The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation ...The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.展开更多
Currently, 1 bit or 2 bit signal quantization is widely used in satellite navigation software receivers. The bit-wise parallel algorithm has been proposed for 1 bit and 2 bit signal quantization, which performs correl...Currently, 1 bit or 2 bit signal quantization is widely used in satellite navigation software receivers. The bit-wise parallel algorithm has been proposed for 1 bit and 2 bit signal quantization, which performs correlation with high efficiency. In order to improve the performance of the correlator, this paper proposes a new 1.5 bit quantization method. Theoretical analyses are made from the aspects of complexity and quantization loss, and performance comparison between 1.5 bit quantization correlator and traditional correlators is discussed. The results show that the 1.5 bit quantization algorithm can save about 30 percent complexity under similar quantization loss, reduce more than 0.5 dB signal noise ratio（SNR） loss under similar complexity. It shows great performance improvement for correlators of satellite navigation software receivers.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
As each type of satellite network has different link features, its data transmission must be designed based on its link features to improve the efficiency of data transferring. The transmission of navigation integrate...As each type of satellite network has different link features, its data transmission must be designed based on its link features to improve the efficiency of data transferring. The transmission of navigation integrated services information （NISI） in a global navigation satellite system （GNSS） with inter-satellite links （ISLs） is studied by taking the real situation of inter-satellite communication links into account. An on-demand computing and buffering centralized route strategy is proposed based on dynamic grouping and the topology evolution law of the GNSS network within which the satellite nodes are operated in the manner of dynamic grouping. Dynamic grouping is based on satellites spatial relationships and the group role of the satellite node changes by turns due to its spatial relationships. The route strategy provides significant advantages of high efficiency, low complexity, and flexi- ble configuration, by which the established GNSS can possess the features and capabilities of feasible deployment, efficient transmission, convenient management, structural invulnerability and flexible expansion.展开更多
A pre-processing procedure is designed for a space-surface bistatic synthetic aperture radar （SS-BSAR） system when a time domain image formation algorithm is employed. Three crucial technical issues relating to the ...A pre-processing procedure is designed for a space-surface bistatic synthetic aperture radar （SS-BSAR） system when a time domain image formation algorithm is employed. Three crucial technical issues relating to the procedure are fully discussed. Firstly, unlike image formation algorithms operating in the frequency domain, a time domain algorithm requires the accurate global navigation satellite system （GNSS） time and position. This paper proposes acquisition of this information using a time-and-spatial transfer with precise ephemeris and interpolation. Secondly, synchronization errors and compensation methods in SS-BSAR are analyzed. Finally, taking the non-ideal factors in the echo and the compatibility of image formation algorithms into account, a matched filter based on the minimum delay is constructed. Experimental result using real data suggest the pre-processing is functioning properly.展开更多
In this paper,we study scene image recognition with knowledge transfer for drone navigation.We divide navigation scenes into three macro-classes,namely outdoor special scenes(OSSs),the space from indoors to outdoors o...In this paper,we study scene image recognition with knowledge transfer for drone navigation.We divide navigation scenes into three macro-classes,namely outdoor special scenes(OSSs),the space from indoors to outdoors or from outdoors to indoors transitional scenes(TSs),and others.However,there are difficulties in how to recognize the TSs,to this end,we employ deep convolutional neural network(CNN)based on knowledge transfer,techniques for image augmentation,and fine tuning to solve the issue.Moreover,there is still a novelty detection prob-lem in the classifier,and we use global navigation satellite sys-tems(GNSS)to solve it in the prediction stage.Experiment results show our method,with a pre-trained model and fine tun-ing,can achieve 91.3196%top-1 accuracy on Scenes21 dataset,paving the way for drones to learn to understand the scenes around them autonomously.展开更多
As high-dynamics and weak-signal are of two primary concerns of navigation using Global Navigation Satellite System(GNSS)signals,an acquisition algorithm based on threetime fractional Fourier transform(FRFT)is present...As high-dynamics and weak-signal are of two primary concerns of navigation using Global Navigation Satellite System(GNSS)signals,an acquisition algorithm based on threetime fractional Fourier transform(FRFT)is presented to simplify the calculation effectively.Firstly,the correlation results similar to linear frequency modulated(LFM)signals are derived on the basis of the high dynamic GNSS signal model.Then,the principle of obtaining the optimum rotation angle is analyzed,which is measured by FRFT projection lengths with two selected rotation angles.Finally,Doppler shift,Doppler rate,and code phase are accurately estimated in a real-time and low signal to noise ratio(SNR)wireless communication system.The theoretical analysis and simulation results show that the fast FRFT algorithm can accurately estimate the high dynamic parameters by converting the traditional two-dimensional search process to only three times FRFT.While the acquisition performance is basically the same,the computational complexity and running time are greatly reduced,which is more conductive to practical application.展开更多
Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation...Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.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
Global positioning system (GPS) for vehicle applications in the urban area is challenged by low signal intensity. The carrier loop based on fast Fourier transform (FFT) can obtain a high signal to noise ratio (SNR) ga...Global positioning system (GPS) for vehicle applications in the urban area is challenged by low signal intensity. The carrier loop based on fast Fourier transform (FFT) can obtain a high signal to noise ratio (SNR) gain by increasing the observation time. However, this leads to a major problem that the acceleration cannot be ignored. The performance of the FFT-based loop will decline with the acceleration increasing. This paper discusses the effect of the dynamic on FFT first. Then a high performance carrier tracking loop for weak GPS L5 signals is proposed. It combines discrete chirp-Fourier transform (DCFT) and the phase fitting method to estimate Doppler frequency and Doppler rate simultaneously. First, a sequence of integration results is used to perform DCFT to estimate coarse Doppler frequency and Doppler rate. Second, the phase of the sequence is calculated and used to perform linear fitting. By the phase fitting method, the fine Doppler frequency and Doppler rate can be estimated. The computation cost is small because the integration results are used and the phase fitting method needs only coarse estimates of Doppler frequency and Doppler rate. Compared with FFT and DCFT, the precision of the phase fitting method is not limited by the resolution. Thus the proposed loop can get high precision and low carrier to noise ratio (C/N-0) tracking threshold. Simulation results show this loop has a great improvement than conventional loops for urban weak-signal applications.展开更多
Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by ...Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by the antenna array. However,the adaptive beamforming will change the array pattern in realtime, which has the potential to introduce phase center biases into the antenna array. For precise applications, these phase biases must be mitigated or compensated because they will bring errors in code phase and carrier phase measurements. A novel adaptive beamforming algorithm is proposed firstly, then the phase bias induced by the proposed algorithm is estimated, and finally a compensation strategy is addressed. Simulations demonstrate that the proposed beamforming algorithm suppresses effectively the strong interference and improves significantly the capturing performance of GNSS signals. Simultaneously, the bias compensation method avoids the loss of the carrier phase lock and reduces the phase measurement errors for GNSS receivers.展开更多
Traditional global navigation satellite system(GNSS)terminals for satellite navigation adopt independent channels to track the signals from different satellites, which results in a lack of information interaction betw...Traditional global navigation satellite system(GNSS)terminals for satellite navigation adopt independent channels to track the signals from different satellites, which results in a lack of information interaction between the channels. Inspired by the vector tracking idea, and drawing lessons from the principle that in the position domain the Taylor expanded pseudorange observations can be used for positioning via the least squares method, this paper proposes a novel least squares-based multi-channel parameter joint estimation(MPJE) method in the signal domain, which not only retains the advantages of channel fusion, but also maintains the flexibility and diversity of the localization algorithm. With achieving optimal carrier to noise ratio as the goal, the proposed method obtains the required code loop and carrier loop parameters for signal tracking in the domain of whole channels. Experimental results indicate that this method fully achieves the assistant fusion advantages of frequency lock loop(FLL), phase lock loop(PLL)and delay lock loop(DLL), making good use of the robustness and dynamic properties of the FLL and the measurement accuracy of the DLL, and is helpful for achieving stable and accurate signal tracking under weak signals and high dynamic stress environments.展开更多
Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooper...Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooperative target motion is usually difficult to be compensated,as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective.Consequently,the moving target in GBPR image is usually defocused,which aggravates the difficulty of target detection even further.In this paper,a spawning particle filter(SPF)is proposed for defocused MTD.Firstly,the measurement model and the likelihood ratio function(LRF)of the defocused point-like target image are deduced.Then,a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF)as their parent.After that,based on the PF estimator,the SPF algorithm and its sequential Monte Carlo(SMC)implementation are proposed with a novel amplitude estimation method to decrease the target state dimension.Finally,the effectiveness of the proposed SPF is demonstrated by numerical simulations and pre-liminary experimental results,showing that the target range and Doppler can be estimated accurately.展开更多
Weak global navigation satellite system（GNSS） signal acquisition has been a limitation for high sensitivity GPS receivers. This paper modifies the traditional acquisition algorithms and proposes a new weak GNSS sign...Weak global navigation satellite system（GNSS） signal acquisition has been a limitation for high sensitivity GPS receivers. This paper modifies the traditional acquisition algorithms and proposes a new weak GNSS signal acquisition method using re-scaling and adaptive stochastic resonance（SR）. The adoption of classical SR is limited to low-frequency and periodic signals. Given that GNSS signal frequency is high and that the periodic feature of the GNSS signal is affected by the Doppler frequency shift, classical SR methods cannot be directly used to acquire GNSS signals. Therefore, the re-scaling technique is used in our study to expand its usage to high-frequency signals and adaptive control technique is used to gradually determine the Doppler shift effect in GNSS signal buried in strong noises. The effectiveness of our proposed method was verified by the simulations on GPS L1 signals. The simulation results indicate that the new algorithm based on SR can reach-181 d BW sensitivity with a very short data length of 1 ms.展开更多
The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of d...The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs(on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter(En KF) is introduced to estimate the vehicle's state with observations from navigation satellites and neighborhood vehicles, and the original En KF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in En KF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.展开更多
In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in th...In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in the signals across different incident directions,resulting in distinct CNR variations for each signal.A model is developed to calculate the variation value of the signal CNR based on the antenna gain pattern.This model enables the differentiation of the variation values of the CNR for authentic satellite signals and spoofing signals,thereby facilitating spoofing detection.The proposed method is capable of detecting spoofing signals with power and CNR similar to those of authentic satellite signals.The accuracy of the signal CNR variation value calculation model and the effectiveness of the spoofing detection method are verified through a series of experiments.In addition,the proposed spoofing detection method works not only for a single spoofing source but also for distributed spoofing sources.展开更多
基金supported by the National Natural Science Foundation of China(41804035,41374027)。
文摘The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.
基金supported by the National Natural Science Foundation of China(61101076413741376147017)
文摘Currently, 1 bit or 2 bit signal quantization is widely used in satellite navigation software receivers. The bit-wise parallel algorithm has been proposed for 1 bit and 2 bit signal quantization, which performs correlation with high efficiency. In order to improve the performance of the correlator, this paper proposes a new 1.5 bit quantization method. Theoretical analyses are made from the aspects of complexity and quantization loss, and performance comparison between 1.5 bit quantization correlator and traditional correlators is discussed. The results show that the 1.5 bit quantization algorithm can save about 30 percent complexity under similar quantization loss, reduce more than 0.5 dB signal noise ratio（SNR） loss under similar complexity. It shows great performance improvement for correlators of satellite navigation software receivers.
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).
文摘As each type of satellite network has different link features, its data transmission must be designed based on its link features to improve the efficiency of data transferring. The transmission of navigation integrated services information （NISI） in a global navigation satellite system （GNSS） with inter-satellite links （ISLs） is studied by taking the real situation of inter-satellite communication links into account. An on-demand computing and buffering centralized route strategy is proposed based on dynamic grouping and the topology evolution law of the GNSS network within which the satellite nodes are operated in the manner of dynamic grouping. Dynamic grouping is based on satellites spatial relationships and the group role of the satellite node changes by turns due to its spatial relationships. The route strategy provides significant advantages of high efficiency, low complexity, and flexi- ble configuration, by which the established GNSS can possess the features and capabilities of feasible deployment, efficient transmission, convenient management, structural invulnerability and flexible expansion.
基金supported by the Electro-Magnetic Remote Sensing Defence Technology Centre (EMRS-DTC) of the UK Ministry of Defence(EMRS/DTC/1/27)the China Scholarship Council (2009611064)the Program for New Century Excellent Talents in University (NCET-07-0223)
文摘A pre-processing procedure is designed for a space-surface bistatic synthetic aperture radar （SS-BSAR） system when a time domain image formation algorithm is employed. Three crucial technical issues relating to the procedure are fully discussed. Firstly, unlike image formation algorithms operating in the frequency domain, a time domain algorithm requires the accurate global navigation satellite system （GNSS） time and position. This paper proposes acquisition of this information using a time-and-spatial transfer with precise ephemeris and interpolation. Secondly, synchronization errors and compensation methods in SS-BSAR are analyzed. Finally, taking the non-ideal factors in the echo and the compatibility of image formation algorithms into account, a matched filter based on the minimum delay is constructed. Experimental result using real data suggest the pre-processing is functioning properly.
基金supported by the National Natural Science Foundation of China(62103104)the Natural Science Foundation of Jiangsu Province(BK20210215)the China Postdoctoral Science Foundation(2021M690615).
文摘In this paper,we study scene image recognition with knowledge transfer for drone navigation.We divide navigation scenes into three macro-classes,namely outdoor special scenes(OSSs),the space from indoors to outdoors or from outdoors to indoors transitional scenes(TSs),and others.However,there are difficulties in how to recognize the TSs,to this end,we employ deep convolutional neural network(CNN)based on knowledge transfer,techniques for image augmentation,and fine tuning to solve the issue.Moreover,there is still a novelty detection prob-lem in the classifier,and we use global navigation satellite sys-tems(GNSS)to solve it in the prediction stage.Experiment results show our method,with a pre-trained model and fine tun-ing,can achieve 91.3196%top-1 accuracy on Scenes21 dataset,paving the way for drones to learn to understand the scenes around them autonomously.
基金supported by Shenzhen Science and Technology Program(JCYJ20180508152046428).
文摘As high-dynamics and weak-signal are of two primary concerns of navigation using Global Navigation Satellite System(GNSS)signals,an acquisition algorithm based on threetime fractional Fourier transform(FRFT)is presented to simplify the calculation effectively.Firstly,the correlation results similar to linear frequency modulated(LFM)signals are derived on the basis of the high dynamic GNSS signal model.Then,the principle of obtaining the optimum rotation angle is analyzed,which is measured by FRFT projection lengths with two selected rotation angles.Finally,Doppler shift,Doppler rate,and code phase are accurately estimated in a real-time and low signal to noise ratio(SNR)wireless communication system.The theoretical analysis and simulation results show that the fast FRFT algorithm can accurately estimate the high dynamic parameters by converting the traditional two-dimensional search process to only three times FRFT.While the acquisition performance is basically the same,the computational complexity and running time are greatly reduced,which is more conductive to practical application.
基金supported by the State Key Laboratory of Geo-Information Engineering(SKLGIE2022-Z-2-1)the National Natural Science Foundation of China(41674024,42174036).
文摘Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.
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(6140134061573059)the Areo Space T.T.&.C.Innovation Program(201515A)
文摘Global positioning system (GPS) for vehicle applications in the urban area is challenged by low signal intensity. The carrier loop based on fast Fourier transform (FFT) can obtain a high signal to noise ratio (SNR) gain by increasing the observation time. However, this leads to a major problem that the acceleration cannot be ignored. The performance of the FFT-based loop will decline with the acceleration increasing. This paper discusses the effect of the dynamic on FFT first. Then a high performance carrier tracking loop for weak GPS L5 signals is proposed. It combines discrete chirp-Fourier transform (DCFT) and the phase fitting method to estimate Doppler frequency and Doppler rate simultaneously. First, a sequence of integration results is used to perform DCFT to estimate coarse Doppler frequency and Doppler rate. Second, the phase of the sequence is calculated and used to perform linear fitting. By the phase fitting method, the fine Doppler frequency and Doppler rate can be estimated. The computation cost is small because the integration results are used and the phase fitting method needs only coarse estimates of Doppler frequency and Doppler rate. Compared with FFT and DCFT, the precision of the phase fitting method is not limited by the resolution. Thus the proposed loop can get high precision and low carrier to noise ratio (C/N-0) tracking threshold. Simulation results show this loop has a great improvement than conventional loops for urban weak-signal applications.
基金supported by the National Natural Science Foundation of China(61301094)the Postdoctoral Science Foundation of China(2014M552490)
文摘Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by the antenna array. However,the adaptive beamforming will change the array pattern in realtime, which has the potential to introduce phase center biases into the antenna array. For precise applications, these phase biases must be mitigated or compensated because they will bring errors in code phase and carrier phase measurements. A novel adaptive beamforming algorithm is proposed firstly, then the phase bias induced by the proposed algorithm is estimated, and finally a compensation strategy is addressed. Simulations demonstrate that the proposed beamforming algorithm suppresses effectively the strong interference and improves significantly the capturing performance of GNSS signals. Simultaneously, the bias compensation method avoids the loss of the carrier phase lock and reduces the phase measurement errors for GNSS receivers.
基金supported by the National Natural Science Foundation of China(41474027)National Defense Basic Science Project of China(JCKY2016110B004)
文摘Traditional global navigation satellite system(GNSS)terminals for satellite navigation adopt independent channels to track the signals from different satellites, which results in a lack of information interaction between the channels. Inspired by the vector tracking idea, and drawing lessons from the principle that in the position domain the Taylor expanded pseudorange observations can be used for positioning via the least squares method, this paper proposes a novel least squares-based multi-channel parameter joint estimation(MPJE) method in the signal domain, which not only retains the advantages of channel fusion, but also maintains the flexibility and diversity of the localization algorithm. With achieving optimal carrier to noise ratio as the goal, the proposed method obtains the required code loop and carrier loop parameters for signal tracking in the domain of whole channels. Experimental results indicate that this method fully achieves the assistant fusion advantages of frequency lock loop(FLL), phase lock loop(PLL)and delay lock loop(DLL), making good use of the robustness and dynamic properties of the FLL and the measurement accuracy of the DLL, and is helpful for achieving stable and accurate signal tracking under weak signals and high dynamic stress environments.
基金supported by the National Natural Science Foundation of China(62101014)the National Key Laboratory of Science and Technology on Space Microwave(6142411203307).
文摘Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooperative target motion is usually difficult to be compensated,as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective.Consequently,the moving target in GBPR image is usually defocused,which aggravates the difficulty of target detection even further.In this paper,a spawning particle filter(SPF)is proposed for defocused MTD.Firstly,the measurement model and the likelihood ratio function(LRF)of the defocused point-like target image are deduced.Then,a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF)as their parent.After that,based on the PF estimator,the SPF algorithm and its sequential Monte Carlo(SMC)implementation are proposed with a novel amplitude estimation method to decrease the target state dimension.Finally,the effectiveness of the proposed SPF is demonstrated by numerical simulations and pre-liminary experimental results,showing that the target range and Doppler can be estimated accurately.
基金supported by the National Natural Science Foundation of China(61202078)
文摘Weak global navigation satellite system（GNSS） signal acquisition has been a limitation for high sensitivity GPS receivers. This paper modifies the traditional acquisition algorithms and proposes a new weak GNSS signal acquisition method using re-scaling and adaptive stochastic resonance（SR）. The adoption of classical SR is limited to low-frequency and periodic signals. Given that GNSS signal frequency is high and that the periodic feature of the GNSS signal is affected by the Doppler frequency shift, classical SR methods cannot be directly used to acquire GNSS signals. Therefore, the re-scaling technique is used in our study to expand its usage to high-frequency signals and adaptive control technique is used to gradually determine the Doppler shift effect in GNSS signal buried in strong noises. The effectiveness of our proposed method was verified by the simulations on GPS L1 signals. The simulation results indicate that the new algorithm based on SR can reach-181 d BW sensitivity with a very short data length of 1 ms.
基金Project(4144081)supported by Beijing Natural Science Foundation,ChinaProjects(61403021,U1334211,61490705)supported by the National Natural Science Foundation of China+1 种基金Project(2015RC015)supported by the Fundamental Research Funds for Central Universities,ChinaProject supported by the Foundation of Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control,China
文摘The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs(on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter(En KF) is introduced to estimate the vehicle's state with observations from navigation satellites and neighborhood vehicles, and the original En KF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in En KF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.
基金supported by the National Natural Science Foundation of China(62273195).
文摘In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in the signals across different incident directions,resulting in distinct CNR variations for each signal.A model is developed to calculate the variation value of the signal CNR based on the antenna gain pattern.This model enables the differentiation of the variation values of the CNR for authentic satellite signals and spoofing signals,thereby facilitating spoofing detection.The proposed method is capable of detecting spoofing signals with power and CNR similar to those of authentic satellite signals.The accuracy of the signal CNR variation value calculation model and the effectiveness of the spoofing detection method are verified through a series of experiments.In addition,the proposed spoofing detection method works not only for a single spoofing source but also for distributed spoofing sources.
