A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization ...A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization of Gabor atom and is more delicate for matching most of the signals encountered in practice, especially for those having frequency dispersion characteristics. The time-frequency distribution of this atom concentrates in its time center and frequency center along energy curve, with the curve being oblique to a certain extent along the time axis. A novel parametric adaptive time-frequency distribution based on a set of the derived atoms is then proposed using a adaptive signal subspace decomposition method in frequency domain, which is non-negative time-frequency energy distribution and free of cross-term interference for multicomponent signals. The results of numerical simulation manifest the effectiveness of the approach in time-frequency representation and signal de-noising processing.展开更多
Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributio...Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributions are introduced for the modulation classification of communication signals： The extracted time-frequency features have good classification information, and they are insensitive to signal to noise ratio （SNR） variation. According to good classification by the correct rate of a neural network classifier, a multilayer perceptron （MLP） classifier with better generalization, as well as, addition of time-frequency features set for classifying six different modulation types has been proposed. Computer simulations show that the MLP classifier outperforms the decision-theoretic classifier at low SNRs, and the classification experiments for real MPSK signals verify engineering significance of the MLP classifier.展开更多
The interrupted sampling repeater jamming（ISRJ） is an effective deception jamming method for coherent radar, especially for the wideband linear frequency modulation（LFM） radar. An electronic counter-countermeasure...The interrupted sampling repeater jamming（ISRJ） is an effective deception jamming method for coherent radar, especially for the wideband linear frequency modulation（LFM） radar. An electronic counter-countermeasure（ECCM） scheme is proposed to remove the ISRJ-based false targets from the pulse compression result of the de-chirping radar. Through the time-frequency（TF） analysis of the radar echo signal, it can be found that the TF characteristics of the ISRJ signal are discontinuous in the pulse duration because the ISRJ jammer needs short durations to receive the radar signal. Based on the discontinuous characteristics a particular band-pass filter can be generated by two alternative approaches to retain the true target signal and suppress the ISRJ signal. The simulation results prove the validity of the proposed ECCM scheme for the ISRJ.展开更多
This paper considers the problem of target and jamming recognition for the pulse Doppler radar fuze(PDRF).To solve the problem,the matched filter outputs of the PDRF under the action of target and jamming are analyzed...This paper considers the problem of target and jamming recognition for the pulse Doppler radar fuze(PDRF).To solve the problem,the matched filter outputs of the PDRF under the action of target and jamming are analyzed.Then,the frequency entropy and peak-to-peak ratio are extracted from the matched filter output of the PDRF,and the time-frequency joint feature is constructed.Based on the time-frequency joint feature,the naive Bayesian classifier(NBC)with minimal risk is established for target and jamming recognition.To improve the adaptability of the proposed method in complex environments,an online update process that adaptively modifies the classifier in the duration of the work of the PDRF is proposed.The experiments show that the PDRF can maintain high recognition accuracy when the signal-to-noise ratio(SNR)decreases and the jamming-to-signal ratio(JSR)increases.Moreover,the applicable analysis shows that he ONBCMR method has low computational complexity and can fully meet the real-time requirements of PDRF.展开更多
This paper deals with the blind separation of nonstation-ary sources and direction-of-arrival （DOA） estimation in the under-determined case, when there are more sources than sensors. We assume the sources to be time...This paper deals with the blind separation of nonstation-ary sources and direction-of-arrival （DOA） estimation in the under-determined case, when there are more sources than sensors. We assume the sources to be time-frequency （TF） disjoint to a certain extent. In particular, the number of sources presented at any TF neighborhood is strictly less than that of sensors. We can identify the real number of active sources and achieve separation in any TF neighborhood by the sparse representation method. Compared with the subspace-based algorithm under the same sparseness assumption, which suffers from the extra noise effect since it can-not estimate the true number of active sources, the proposed algorithm can estimate the number of active sources and their cor-responding TF values in any TF neighborhood simultaneously. An-other contribution of this paper is a new estimation procedure for the DOA of sources in the underdetermined case, which combines the TF sparseness of sources and the clustering technique. Sim-ulation results demonstrate the validity and high performance of the proposed algorithm in both blind source separation （BSS） and DOA estimation.展开更多
Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributio...Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.展开更多
This paper proposes a scheme to construct time- frequency codes based on protograph low density parity check （LDPC） codes in orthogonal frequency division multiplexing （OFDM） communication systems. This approach s...This paper proposes a scheme to construct time- frequency codes based on protograph low density parity check （LDPC） codes in orthogonal frequency division multiplexing （OFDM） communication systems. This approach synthesizes two techniques： protograph LDPC codes and OFDM. One symbol of encoded information by protograph LDPC codes corresponds to one sub-carrier, namely the length of encoded information equals to the number of sub-carriers. The design of good protograph LDPC codes with short lengths is given, and the proposed proto- graph LDPC codes can be of fast encoding, which can reduce the encoding complexity and simplify encoder hardware implementa- tion. The proposed approach provides a higher coding gain in the Rayleigh fading channel. The simulation results in the Rayleigh fading channel show that the bit error rate （BER） performance of the proposed time-frequency codes is as good as random LDPC- OFDM codes and is better than Tanner LDPC-OFDM codes under the condition of different fading coefficients.展开更多
As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardne...As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.展开更多
Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The ...Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.展开更多
This paper proposes a new method for estimating the parameter of maneuvering targets based on sparse time-frequency transform in over-the-horizon radar（OTHR）. In this method, the sparse time-frequency distribution o...This paper proposes a new method for estimating the parameter of maneuvering targets based on sparse time-frequency transform in over-the-horizon radar（OTHR）. In this method, the sparse time-frequency distribution of the radar echo is obtained by solving a sparse optimization problem based on the short-time Fourier transform. Then Hough transform is employed to estimate the parameter of the targets. The proposed algorithm has the following advantages： Compared with the Wigner-Hough transform method, the computational complexity of the sparse optimization is low due to the application of fast Fourier transform（FFT）. And the computational cost of Hough transform is also greatly reduced because of the sparsity of the time-frequency distribution. Compared with the high order ambiguity function（HAF） method, the proposed method improves in terms of precision and robustness to noise. Simulation results show that compared with the HAF method, the required SNR and relative mean square error are 8 dB lower and 50 dB lower respectively in the proposed method. While processing the field experiment data, the execution time of Hough transform in the proposed method is only 4% of the Wigner-Hough transform method.展开更多
In this paper, propagated δ pulses through different distance of plasma are calculated,and their time-frequency characteristics are studied using CWD (Choi-William distribution). It is found that several horizontal s...In this paper, propagated δ pulses through different distance of plasma are calculated,and their time-frequency characteristics are studied using CWD (Choi-William distribution). It is found that several horizontal spectra appear at early arrival time like discrete spectrum, at last time a hyperbolic curve lies in the time-frequency spectrum which corresponds to the frequency-group delay curve of plasma. To understand the time-frequency the property of a signal is helpful for obtaining the plasma parameters.展开更多
The application scope of the forward scatter radar(FSR)based on the Global Navigation Satellite System(GNSS)can be expanded by improving the detection capability.Firstly,the forward-scatter signal model when the targe...The application scope of the forward scatter radar(FSR)based on the Global Navigation Satellite System(GNSS)can be expanded by improving the detection capability.Firstly,the forward-scatter signal model when the target crosses the baseline is constructed.Then,the detection method of the for-ward-scatter signal based on the Rényi entropy of time-fre-quency distribution is proposed and the detection performance with different time-frequency distributions is compared.Simula-tion results show that the method based on the smooth pseudo Wigner-Ville distribution(SPWVD)can achieve the best perfor-mance.Next,combined with the geometry of FSR,the influence on detection performance of the relative distance between the target and the baseline is analyzed.Finally,the proposed method is validated by the anechoic chamber measurements and the results show that the detection ability has a 10 dB improvement compared with the common constant false alarm rate(CFAR)detection.展开更多
The warhead of a ballistic missile may precess due to lateral moments during release. The resulting micro-Doppler effect is determined by parameters such as the target's motion state and size. A three-dimensional ...The warhead of a ballistic missile may precess due to lateral moments during release. The resulting micro-Doppler effect is determined by parameters such as the target's motion state and size. A three-dimensional reconstruction method for the precession warhead via the micro-Doppler analysis and inverse Radon transform(IRT) is proposed in this paper. The precession parameters are extracted by the micro-Doppler analysis from three radars, and the IRT is used to estimate the size of targe. The scatterers of the target can be reconstructed based on the above parameters. Simulation experimental results illustrate the effectiveness of the proposed method in this paper.展开更多
Modern radar signals mostly use low probability of intercept(LPI)waveforms,which have short pulses in the time domain,multicomponent properties,frequency hopping,combined modulation waveforms and other characteristics...Modern radar signals mostly use low probability of intercept(LPI)waveforms,which have short pulses in the time domain,multicomponent properties,frequency hopping,combined modulation waveforms and other characteristics,making the detection and estimation of LPI radar signals extremely difficult,and leading to highly required significant research on perception technology in the battlefield environment.This paper proposes a visibility graphs(VG)-based multicomponent signals detection method and a modulation waveforms parameter estimation algorithm based on the time-frequency representation(TFR).On the one hand,the frequency domain VG is used to set the dynamic threshold for detecting the multicomponent LPI radar waveforms.On the other hand,the signal is projected into the time and frequency domains by the TFR method for estimating its symbol width and instantaneous frequency(IF).Simulation performance shows that,compared with the most advanced methods,the algorithm proposed in this paper has a valuable advantage.Meanwhile,the calculation cost of the algorithm is quite low,and it is achievable in the future battlefield.展开更多
This paper introduces the time-frequency analyzed long short-term memory(TF-LSTM) neural network method for jamming signal recognition over the Global Navigation Satellite System(GNSS) receiver. The method introduces ...This paper introduces the time-frequency analyzed long short-term memory(TF-LSTM) neural network method for jamming signal recognition over the Global Navigation Satellite System(GNSS) receiver. The method introduces the long shortterm memory(LSTM) neural network into the recognition algorithm and combines the time-frequency(TF) analysis for signal preprocessing. Five kinds of navigation jamming signals including white Gaussian noise(WGN), pulse jamming, sweep jamming, audio jamming, and spread spectrum jamming are used as input for training and recognition. Since the signal parameters and quantity are unknown in the actual scenario, this work builds a data set containing multiple kinds and parameters jamming to train the TF-LSTM. The performance of this method is evaluated by simulations and experiments. The method has higher recognition accuracy and better robustness than the existing methods, such as LSTM and the convolutional neural network(CNN).展开更多
Nyquist Folding Receiver(NYFR)is a perceptron structure that realizes a low probability of intercept(LPI)signal analog to information.Aiming at the problem of LPI radar signal receiving,the time domain,frequency domai...Nyquist Folding Receiver(NYFR)is a perceptron structure that realizes a low probability of intercept(LPI)signal analog to information.Aiming at the problem of LPI radar signal receiving,the time domain,frequency domain,and time-frequency domain problems of signals intercepted by NYFR structure are studied.Combined with the time-frequency analysis(TFA)method,a radar recognition scheme based on deep learning(DL)is introduced,which can reliably classify common LPI radar signals.First,the structure of NYFR and its characteristics in the time domain,frequency domain,and time and frequency domain are analyzed.Then,the received signal is then converted into a time-frequency image(TFI).Finally,four kinds of DL algorithms are used to classify LPI radar signals.Simulation results demonstrate the correctness of the NYFR structure,and the effectiveness of the proposed recognition method is verified by comparison experiments.展开更多
The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Neverthele...The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Nevertheless,the radial magnetometer signal is modulated by the high-speed rotation,thus the roll angular rate can be achieved by extracting the instantaneous frequency of the radial magnetometer signal.The objective of this study is to find out a precise instantaneous frequency extraction method to obtain an accurate roll angular rate.To reach this goal,a modified spline-kernelled chirplet transform(MSCT)algorithm is proposed in this paper.Due to the nonlinear frequency modulation characteristics of the radial magnetometer signal,the existing time-frequency analysis methods in literature cannot obtain an excellent energy concentration in the time-frequency plane,thereby leading to a terrible instantaneous frequency extraction accuracy.However,the MSCT can overcome the problem of bad energy concentration by replacing the short-time Fourier transform operator with the Chirp Z-transform operator based on the original spline-kernelled chirplet transform.The introduction of Chirp Z-transform can improve the construction accuracy of the transform kernel.Since the construction accuracy of the transform kernel determines the concentration of time-frequency distribution,the MSCT can obtain a more precise instantaneous frequency.The performance of the MSCT was evaluated by a series of numerical simulations,high-speed turntable experiments,and real flight tests.The evaluation results show that the MSCT has an excellent ability to process the nonlinear frequency modulation signal,and can accurately extract the roll angular rate for the high spinning projectiles.展开更多
A new time-frequency transform, known as short-time Lv transform （STLVT）, is proposed by applying the inverse Lv distribution to process consecutive segments of long data sequence. Compared with other time-frequency...A new time-frequency transform, known as short-time Lv transform （STLVT）, is proposed by applying the inverse Lv distribution to process consecutive segments of long data sequence. Compared with other time-frequency representations, the STLVT is able to achieve better energy concentration in the time-frequency domain for signals containing multiple linear and/or non-linear frequency modulated components. The merits of the STLVT are demonstrated in terms of the effects of window length and overlap length between adjacent segments on signal energy concentration in the time-frequency domain, and the required computational complexity. An application on the spectrum sensing for cognitive ratio （CR） by using a joint use of the STLVT and Hough transform （HT） is proposed and simulated.展开更多
The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs wi...The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs with strong scattering contributions.This paper presents an SC modeling approach to acquire the weak SCs of LDTs.We employ the induced currents at the LDT to search SCs,and the joint time-frequency transform together with the Hough transform to separate the scattering contributions of different SCs.Particle swarm optimization(PSO)is applied to improve the estimation results of SCs.The accuracy of the SC model built by this approach is verified by a full-wave numerical method.The validation results show that the SC model of the LDT can precisely simulate the signatures of high-resolution images,such as high-resolution range profile and inverse synthetic aperture radar(ISAR)images.展开更多
Multiple maneuvedng targets signal processing in high frequency radar is challenging due to the following difficulties： the interference between signals is severe because of significant spread of the target Doppler s...Multiple maneuvedng targets signal processing in high frequency radar is challenging due to the following difficulties： the interference between signals is severe because of significant spread of the target Doppler spectrum, the low signal to clutter ratio （SCR） environment degrades the performance of signal process- ing algorithms. This paper addresses this challenging problem by using an S2-method and an adaptive clutter rejection scheme. The proposed S2-method improves the S-method by eliminating inter- ference between signals, and thus it enables multi-target signals to be reconstructed individually. The proposed adaptive clutter rejec- tion scheme is based on an adaptive notch filter, which is designed according to the envelop of the clutter spectrum. Experiments with simulated targets added into radar sea clutter echo and real air target data illustrate the effectiveness of the proposed method.展开更多
基金This project was supported by the National Natural Science Foundation of China (60472102)Shanghai Leading Academic Discipline Project (T0103).
文摘A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization of Gabor atom and is more delicate for matching most of the signals encountered in practice, especially for those having frequency dispersion characteristics. The time-frequency distribution of this atom concentrates in its time center and frequency center along energy curve, with the curve being oblique to a certain extent along the time axis. A novel parametric adaptive time-frequency distribution based on a set of the derived atoms is then proposed using a adaptive signal subspace decomposition method in frequency domain, which is non-negative time-frequency energy distribution and free of cross-term interference for multicomponent signals. The results of numerical simulation manifest the effectiveness of the approach in time-frequency representation and signal de-noising processing.
文摘Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributions are introduced for the modulation classification of communication signals： The extracted time-frequency features have good classification information, and they are insensitive to signal to noise ratio （SNR） variation. According to good classification by the correct rate of a neural network classifier, a multilayer perceptron （MLP） classifier with better generalization, as well as, addition of time-frequency features set for classifying six different modulation types has been proposed. Computer simulations show that the MLP classifier outperforms the decision-theoretic classifier at low SNRs, and the classification experiments for real MPSK signals verify engineering significance of the MLP classifier.
基金supported by the National Natural Science Foundation of China(61271442)
文摘The interrupted sampling repeater jamming（ISRJ） is an effective deception jamming method for coherent radar, especially for the wideband linear frequency modulation（LFM） radar. An electronic counter-countermeasure（ECCM） scheme is proposed to remove the ISRJ-based false targets from the pulse compression result of the de-chirping radar. Through the time-frequency（TF） analysis of the radar echo signal, it can be found that the TF characteristics of the ISRJ signal are discontinuous in the pulse duration because the ISRJ jammer needs short durations to receive the radar signal. Based on the discontinuous characteristics a particular band-pass filter can be generated by two alternative approaches to retain the true target signal and suppress the ISRJ signal. The simulation results prove the validity of the proposed ECCM scheme for the ISRJ.
基金supported by the National Natural Science Foundation of China(Grant No.61973037 and No.61673066).
文摘This paper considers the problem of target and jamming recognition for the pulse Doppler radar fuze(PDRF).To solve the problem,the matched filter outputs of the PDRF under the action of target and jamming are analyzed.Then,the frequency entropy and peak-to-peak ratio are extracted from the matched filter output of the PDRF,and the time-frequency joint feature is constructed.Based on the time-frequency joint feature,the naive Bayesian classifier(NBC)with minimal risk is established for target and jamming recognition.To improve the adaptability of the proposed method in complex environments,an online update process that adaptively modifies the classifier in the duration of the work of the PDRF is proposed.The experiments show that the PDRF can maintain high recognition accuracy when the signal-to-noise ratio(SNR)decreases and the jamming-to-signal ratio(JSR)increases.Moreover,the applicable analysis shows that he ONBCMR method has low computational complexity and can fully meet the real-time requirements of PDRF.
基金supported by the National Natural Science Foundation of China(61072120)
文摘This paper deals with the blind separation of nonstation-ary sources and direction-of-arrival （DOA） estimation in the under-determined case, when there are more sources than sensors. We assume the sources to be time-frequency （TF） disjoint to a certain extent. In particular, the number of sources presented at any TF neighborhood is strictly less than that of sensors. We can identify the real number of active sources and achieve separation in any TF neighborhood by the sparse representation method. Compared with the subspace-based algorithm under the same sparseness assumption, which suffers from the extra noise effect since it can-not estimate the true number of active sources, the proposed algorithm can estimate the number of active sources and their cor-responding TF values in any TF neighborhood simultaneously. An-other contribution of this paper is a new estimation procedure for the DOA of sources in the underdetermined case, which combines the TF sparseness of sources and the clustering technique. Sim-ulation results demonstrate the validity and high performance of the proposed algorithm in both blind source separation （BSS） and DOA estimation.
基金This work was supported by the National Natural Science Foundation of China(91538201)the Taishan Scholar Project of Shandong Province(ts201511020)the project supported by Chinese National Key Laboratory of Science and Technology on Information System Security(6142111190404).
文摘Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.
基金supported by the Beijing Natural Science Foundation of China (4102050)the National Natural Science of Foundation of China (NSFC)-Korea Science and Engineering Foundation (KOSF) Joint Research Project of China and Korea (60811140343)
文摘This paper proposes a scheme to construct time- frequency codes based on protograph low density parity check （LDPC） codes in orthogonal frequency division multiplexing （OFDM） communication systems. This approach synthesizes two techniques： protograph LDPC codes and OFDM. One symbol of encoded information by protograph LDPC codes corresponds to one sub-carrier, namely the length of encoded information equals to the number of sub-carriers. The design of good protograph LDPC codes with short lengths is given, and the proposed proto- graph LDPC codes can be of fast encoding, which can reduce the encoding complexity and simplify encoder hardware implementa- tion. The proposed approach provides a higher coding gain in the Rayleigh fading channel. The simulation results in the Rayleigh fading channel show that the bit error rate （BER） performance of the proposed time-frequency codes is as good as random LDPC- OFDM codes and is better than Tanner LDPC-OFDM codes under the condition of different fading coefficients.
基金supported by the National Natural Science Foundation of China(61472443)the Basic Research Priorities Program of Shaanxi Province Natural Science Foundation of China(2013JQ8042)
文摘As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.
文摘Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.
基金supported by the National Natural Science Foundation of China(611011726137118461301262)
文摘This paper proposes a new method for estimating the parameter of maneuvering targets based on sparse time-frequency transform in over-the-horizon radar（OTHR）. In this method, the sparse time-frequency distribution of the radar echo is obtained by solving a sparse optimization problem based on the short-time Fourier transform. Then Hough transform is employed to estimate the parameter of the targets. The proposed algorithm has the following advantages： Compared with the Wigner-Hough transform method, the computational complexity of the sparse optimization is low due to the application of fast Fourier transform（FFT）. And the computational cost of Hough transform is also greatly reduced because of the sparsity of the time-frequency distribution. Compared with the high order ambiguity function（HAF） method, the proposed method improves in terms of precision and robustness to noise. Simulation results show that compared with the HAF method, the required SNR and relative mean square error are 8 dB lower and 50 dB lower respectively in the proposed method. While processing the field experiment data, the execution time of Hough transform in the proposed method is only 4% of the Wigner-Hough transform method.
文摘In this paper, propagated δ pulses through different distance of plasma are calculated,and their time-frequency characteristics are studied using CWD (Choi-William distribution). It is found that several horizontal spectra appear at early arrival time like discrete spectrum, at last time a hyperbolic curve lies in the time-frequency spectrum which corresponds to the frequency-group delay curve of plasma. To understand the time-frequency the property of a signal is helpful for obtaining the plasma parameters.
基金This work was supported by the National Natural Science Foundation of China(62071475,61890541,62171447).
文摘The application scope of the forward scatter radar(FSR)based on the Global Navigation Satellite System(GNSS)can be expanded by improving the detection capability.Firstly,the forward-scatter signal model when the target crosses the baseline is constructed.Then,the detection method of the for-ward-scatter signal based on the Rényi entropy of time-fre-quency distribution is proposed and the detection performance with different time-frequency distributions is compared.Simula-tion results show that the method based on the smooth pseudo Wigner-Ville distribution(SPWVD)can achieve the best perfor-mance.Next,combined with the geometry of FSR,the influence on detection performance of the relative distance between the target and the baseline is analyzed.Finally,the proposed method is validated by the anechoic chamber measurements and the results show that the detection ability has a 10 dB improvement compared with the common constant false alarm rate(CFAR)detection.
基金supported by the National Natural Science Foundation of China (61871146)the Fundamental Research Funds for the Central Universities (FRFCU5710093720)。
文摘The warhead of a ballistic missile may precess due to lateral moments during release. The resulting micro-Doppler effect is determined by parameters such as the target's motion state and size. A three-dimensional reconstruction method for the precession warhead via the micro-Doppler analysis and inverse Radon transform(IRT) is proposed in this paper. The precession parameters are extracted by the micro-Doppler analysis from three radars, and the IRT is used to estimate the size of targe. The scatterers of the target can be reconstructed based on the above parameters. Simulation experimental results illustrate the effectiveness of the proposed method in this paper.
基金supported by the National Defence Pre-research Foundation of China(30502010103).
文摘Modern radar signals mostly use low probability of intercept(LPI)waveforms,which have short pulses in the time domain,multicomponent properties,frequency hopping,combined modulation waveforms and other characteristics,making the detection and estimation of LPI radar signals extremely difficult,and leading to highly required significant research on perception technology in the battlefield environment.This paper proposes a visibility graphs(VG)-based multicomponent signals detection method and a modulation waveforms parameter estimation algorithm based on the time-frequency representation(TFR).On the one hand,the frequency domain VG is used to set the dynamic threshold for detecting the multicomponent LPI radar waveforms.On the other hand,the signal is projected into the time and frequency domains by the TFR method for estimating its symbol width and instantaneous frequency(IF).Simulation performance shows that,compared with the most advanced methods,the algorithm proposed in this paper has a valuable advantage.Meanwhile,the calculation cost of the algorithm is quite low,and it is achievable in the future battlefield.
基金supported by the National Natural Science Foundation of China (62003354)。
文摘This paper introduces the time-frequency analyzed long short-term memory(TF-LSTM) neural network method for jamming signal recognition over the Global Navigation Satellite System(GNSS) receiver. The method introduces the long shortterm memory(LSTM) neural network into the recognition algorithm and combines the time-frequency(TF) analysis for signal preprocessing. Five kinds of navigation jamming signals including white Gaussian noise(WGN), pulse jamming, sweep jamming, audio jamming, and spread spectrum jamming are used as input for training and recognition. Since the signal parameters and quantity are unknown in the actual scenario, this work builds a data set containing multiple kinds and parameters jamming to train the TF-LSTM. The performance of this method is evaluated by simulations and experiments. The method has higher recognition accuracy and better robustness than the existing methods, such as LSTM and the convolutional neural network(CNN).
基金supported by the National Defence Pre-research Foundation of China。
文摘Nyquist Folding Receiver(NYFR)is a perceptron structure that realizes a low probability of intercept(LPI)signal analog to information.Aiming at the problem of LPI radar signal receiving,the time domain,frequency domain,and time-frequency domain problems of signals intercepted by NYFR structure are studied.Combined with the time-frequency analysis(TFA)method,a radar recognition scheme based on deep learning(DL)is introduced,which can reliably classify common LPI radar signals.First,the structure of NYFR and its characteristics in the time domain,frequency domain,and time and frequency domain are analyzed.Then,the received signal is then converted into a time-frequency image(TFI).Finally,four kinds of DL algorithms are used to classify LPI radar signals.Simulation results demonstrate the correctness of the NYFR structure,and the effectiveness of the proposed recognition method is verified by comparison experiments.
基金National Natural Science Foundation(NNSF)of China under Grant 61771059National Natural Science Foundation(NNSF)of China under Grant 61471046Beijing Natural Science Foundation under Grant 4172022 to provide fund for conducting experiments。
文摘The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Nevertheless,the radial magnetometer signal is modulated by the high-speed rotation,thus the roll angular rate can be achieved by extracting the instantaneous frequency of the radial magnetometer signal.The objective of this study is to find out a precise instantaneous frequency extraction method to obtain an accurate roll angular rate.To reach this goal,a modified spline-kernelled chirplet transform(MSCT)algorithm is proposed in this paper.Due to the nonlinear frequency modulation characteristics of the radial magnetometer signal,the existing time-frequency analysis methods in literature cannot obtain an excellent energy concentration in the time-frequency plane,thereby leading to a terrible instantaneous frequency extraction accuracy.However,the MSCT can overcome the problem of bad energy concentration by replacing the short-time Fourier transform operator with the Chirp Z-transform operator based on the original spline-kernelled chirplet transform.The introduction of Chirp Z-transform can improve the construction accuracy of the transform kernel.Since the construction accuracy of the transform kernel determines the concentration of time-frequency distribution,the MSCT can obtain a more precise instantaneous frequency.The performance of the MSCT was evaluated by a series of numerical simulations,high-speed turntable experiments,and real flight tests.The evaluation results show that the MSCT has an excellent ability to process the nonlinear frequency modulation signal,and can accurately extract the roll angular rate for the high spinning projectiles.
基金supported by the National Natural Science Foundation of China(61571174)the Zhejiang Provincial Natural Science Foundation of China(LY15F010010)+3 种基金the Open Project of Zhejiang Key Laboratory for Signal Processing(ZJKL 4 SP–OP2013–02)the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry[2013]693 and[2015]1098the Fundamental Research Funds for the Central Universities(ZYGX2014J097)the Technology Foundation for Selected Overseas Chinese Scholar
文摘A new time-frequency transform, known as short-time Lv transform （STLVT）, is proposed by applying the inverse Lv distribution to process consecutive segments of long data sequence. Compared with other time-frequency representations, the STLVT is able to achieve better energy concentration in the time-frequency domain for signals containing multiple linear and/or non-linear frequency modulated components. The merits of the STLVT are demonstrated in terms of the effects of window length and overlap length between adjacent segments on signal energy concentration in the time-frequency domain, and the required computational complexity. An application on the spectrum sensing for cognitive ratio （CR） by using a joint use of the STLVT and Hough transform （HT） is proposed and simulated.
基金This work was supported by the National Key R&D Program of China(2017YFB0202500)the National Natural Science Foundation of China(61771052).
文摘The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs with strong scattering contributions.This paper presents an SC modeling approach to acquire the weak SCs of LDTs.We employ the induced currents at the LDT to search SCs,and the joint time-frequency transform together with the Hough transform to separate the scattering contributions of different SCs.Particle swarm optimization(PSO)is applied to improve the estimation results of SCs.The accuracy of the SC model built by this approach is verified by a full-wave numerical method.The validation results show that the SC model of the LDT can precisely simulate the signatures of high-resolution images,such as high-resolution range profile and inverse synthetic aperture radar(ISAR)images.
基金supported by the State Key Program of National Natural Science Foundation of China(61032011)
文摘Multiple maneuvedng targets signal processing in high frequency radar is challenging due to the following difficulties： the interference between signals is severe because of significant spread of the target Doppler spectrum, the low signal to clutter ratio （SCR） environment degrades the performance of signal process- ing algorithms. This paper addresses this challenging problem by using an S2-method and an adaptive clutter rejection scheme. The proposed S2-method improves the S-method by eliminating inter- ference between signals, and thus it enables multi-target signals to be reconstructed individually. The proposed adaptive clutter rejec- tion scheme is based on an adaptive notch filter, which is designed according to the envelop of the clutter spectrum. Experiments with simulated targets added into radar sea clutter echo and real air target data illustrate the effectiveness of the proposed method.
