Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the ...Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.展开更多
Separation and recognition of radar signals is the key function of modern radar reconnaissance,which is of great sig-nificance for electronic countermeasures and anti-countermea-sures.In order to improve the ability o...Separation and recognition of radar signals is the key function of modern radar reconnaissance,which is of great sig-nificance for electronic countermeasures and anti-countermea-sures.In order to improve the ability of separating mixed signals in complex electromagnetic environment,a blind source separa-tion algorithm based on degree of cyclostationarity(DCS)crite-rion is constructed in this paper.Firstly,the DCS criterion is con-structed by using the cyclic spectrum theory.Then the algo-rithm flow of blind source separation is designed based on DCS criterion.At the same time,Givens matrix is constructed to make the blind source separation algorithm suitable for multiple sig-nals with different cyclostationary frequencies.The feasibility of this method is further proved.The theoretical and simulation results show that the algorithm can effectively separate and re-cognize common multi-radar signals.展开更多
Source location is the core foundation of microseismic monitoring.To date,commonly used location methods have usually been based on the ray-tracing travel-time technique,which generally adopts an L1 or L2 norm to esta...Source location is the core foundation of microseismic monitoring.To date,commonly used location methods have usually been based on the ray-tracing travel-time technique,which generally adopts an L1 or L2 norm to establish the location objective function.However,the L1 norm usually achieves low location accuracy,whereas the L2 norm is easily affected by large P-wave arrival-time picking errors.In addition,traditional location methods may be affected by the initial iteration point used to find a local optimum location.Furthermore,the P-wave arrival-time data that have travelled long distances are usually poor in quality.To address these problems,this paper presents a microseismic source location method using the Log-Cosh function and distant sensor-removed P-wave arrival data.Its basic principles are as follows:First,the source location objective function is established using the Log-Cosh function.This function has the stability of the L1 norm and location accuracy of the L2 norm.Then,multiple initial points are generated randomly in the mining area,and the established Log-Cosh location objective function is used to obtain multiple corresponding location results.The average value of the 50 location points with the largest data field potential values is treated as the initial location result.Next,the P-wave travel times from the initial location result to triggered sensors are calculated,and then the P-wave arrival data with travel times exceeding 0.2 s are removed.Finally,the aforementioned location steps are repeated with the denoised P-wave arrival dataset to obtain a high-precision location result.Two synthetic events and eight blasting events from the Yongshaba mine,China,were used to test the proposed method.Regardless of whether the P-wave arrival data with long travel times were eliminated,the location error of the proposed method was smaller than that of the L1/L2 norm and trigger-time-based location method(TT1/TT2 method).Furthermore,after eliminating the Pwave arrival data with long travel distances,the location accuracy of these three location methods increased,indicating that the proposed location method has good application prospects.展开更多
A new method based on phase difference analysis is proposed for the single-channel mixed signal separation of single-channel radar fuze.This method is used to estimate the mixing coefficients of de-noised signals thro...A new method based on phase difference analysis is proposed for the single-channel mixed signal separation of single-channel radar fuze.This method is used to estimate the mixing coefficients of de-noised signals through the cumulants of mixed signals,solve the candidate data set by the mixing coefficients and signal analytical form,and resolve the problem of vector ambiguity by analyzing the phase differences.The signal separation is realized by exchanging data of the solutions.The waveform similarity coefficients are calculated,and the time鈥攆requency distributions of separated signals are analyzed.The results show that the proposed method is effective.展开更多
in order to achieve a more efficient way to accurately detect the position of the fire source of spontaneous combustion underground mine, a simple fire source locating method, based on infrared scanning system which c...in order to achieve a more efficient way to accurately detect the position of the fire source of spontaneous combustion underground mine, a simple fire source locating method, based on infrared scanning system which can determine the point where the highest temperature on the surface of igniting ores occurs, was proposed. First, the differential equations that describe heat flow in ore body were presented and the relationship between the surface temperature distribution and the depth and intensity of inner fire source was established with a relatively simple heat transfer model. With the solution of equation, the expression of the relationship between the surface temperature distribution and the inner fire source was deduced and the mathematical-physical model of heat transfer process was set up. Then, with the model, visualization of fire source on the basis of MATLAB simulation platform was realized. The results show that： 1） within 10 m, when the detecting depth is less than 2 m, the temperature perturbation on ores surface can change rapidly, and then slowly; after 4 m, in contrast, it changes very little, and is even close to zero at 10 m; 2） When it is close to self-ignition duration and the detective depths are 2, 5 and 10 m, respectively, the maximum temperature differences are correspondingly 0.5, 0.04 and 0.005 ℃ in the scope of 1 m×1 m; under the same condition, the maximum temperature differences are 1.391, 0.136 and 0.018 ℃, respectively, in the scope of 2 m×2 m. Therefore, this system can be used to measure the temperature differences on the surface of ore body and determine the highest temperature point directly. Also, it is possible to determine the depth of fire source and its intensity by locating method of fire source indirectly.展开更多
We have developed a type of L-shaped single-component geophone array as a single station(L-array station)for surface microseismic monitoring.The L-array station consists of two orthogonal sensor arrays,each being a li...We have developed a type of L-shaped single-component geophone array as a single station(L-array station)for surface microseismic monitoring.The L-array station consists of two orthogonal sensor arrays,each being a linear array of single-component sensors.L-array stations can be used to accurately estimate the polarization of first arrivals without amplitude picking.In a synthetic example,we first use segmentally iterative ray tracing(SIRT)method and forward model to calculate the travel time and polarization of first arrivals at a set of L-array stations.Then,for each L-array station,the relative delay times of first arrivals along sensor arrays are used to estimate the polarization vector.The small errors in estimated polarization vectors show the reliability and robustness of polarization estimation based on L-array stations.We then use reverse-time ray-tracing(RTRT)method to locate the source position based on estimated polarizations at a set of L-array stations.Very small errors in inverted source location and origin time indicate the great potential of L-array stations for source localization applications in surface microseismic monitoring.展开更多
Most of the near-field source localization methods are developed with the approximated signal model,because the phases of the received near-field signal are highly non-linear.Nevertheless,the approximated signal model...Most of the near-field source localization methods are developed with the approximated signal model,because the phases of the received near-field signal are highly non-linear.Nevertheless,the approximated signal model based methods suffer from model mismatch and performance degradation while the exact signal model based estimation methods usually involve parameter searching or multiple decomposition procedures.In this paper,a search-free near-field source localization method is proposed with the exact signal model.Firstly,the approximative estimates of the direction of arrival(DOA)and range are obtained by using the approximated signal model based method through parameter separation and polynomial rooting operations.Then,the approximative estimates are corrected with the exact signal model according to the exact expressions of phase difference in near-field observations.The proposed method avoids spectral searching and parameter pairing and has enhanced estimation performance.Numerical simulations are provided to demonstrate the effectiveness of the proposed method.展开更多
Analyzed the relation between time delay difference and time delay estimation errors, based on the principles of three-point locating, a reformed threshold method for time delay difference estimation of impulse signal...Analyzed the relation between time delay difference and time delay estimation errors, based on the principles of three-point locating, a reformed threshold method for time delay difference estimation of impulse signals, called as amendment estimation for short, is developed by introducing channel equalization technique to its conventional version, named as direct estimation in this paper, to improve the estimation stability. After inherent relationship between time delay and phase shift of signals is analyzed, an integer period error compensation method utilized the diversities of both contribution share and contribution mode of concerned estimates is proposed under the condition of high precision phase lag estimation. Finally, a cooperative multi-threshold estimation method composed of amendment and direct estimations to process impulse signals with three thresholds is established. In sea trials data tests of passive locating, this method improves the estimation precision of time delay difference efficiently. The experiments verify the theoretical predictions.展开更多
With the emergence of location-based applications in various fields, the higher accuracy of positioning is demanded. By utilizing the time differences of arrival （TDOAs） and gain ratios of arrival （GROAs）, an effi...With the emergence of location-based applications in various fields, the higher accuracy of positioning is demanded. By utilizing the time differences of arrival （TDOAs） and gain ratios of arrival （GROAs）, an efficient algorithm for estimating the position is proposed, which exploits the Broyden-Fletcher-Goldfarb-Shanno （BFGS） quasi-Newton method to solve nonlinear equations at the source location under the additive measurement error. Although the accuracy of two-step weighted-least-square （WLS） method based on TDOAs and GROAs is very high, this method has a high computational complexity. While the proposed approach can achieve the same accuracy and bias with the lower computational complexity when the signal-to-noise ratio （SNR） is high, especially it can achieve better accuracy and smaller bias at a lower SNR. The proposed algorithm can be applied to the actual environment due to its real-time property and good robust performance. Simulation results show that with a good initial guess to begin with, the proposed estimator converges to the true solution and achieves the Cramer-Rao lower bound （CRLB） accuracy for both near-field and far-field sources.展开更多
In most literature about joint direction of arrival（DOA） and polarization estimation, the case that sources possess different power levels is seldom discussed. However, this case exists widely in practical applicati...In most literature about joint direction of arrival（DOA） and polarization estimation, the case that sources possess different power levels is seldom discussed. However, this case exists widely in practical applications, especially in passive radar systems. In this paper, we propose a joint DOA and polarization estimation method for unequal power sources based on the reconstructed noise subspace. The invariance property of noise subspace（IPNS） to power of sources has been proved an effective method to estimate DOA of unequal power sources. We develop the IPNS method for joint DOA and polarization estimation based on a dual polarized array. Moreover, we propose an improved IPNS method based on the reconstructed noise subspace, which has higher resolution probability than the IPNS method. It is theoretically proved that the IPNS to power of sources is still valid when the eigenvalues of the noise subspace are changed artificially. Simulation results show that the resolution probability of the proposed method is enhanced compared with the methods based on the IPNS and the polarimetric multiple signal classification（MUSIC） method. Meanwhile, the proposed method has approximately the same estimation accuracy as the IPNS method for the weak source.展开更多
基金National Natural Science Foundation of China under Grant No.61973037China Postdoctoral Science Foundation under Grant No.2022M720419。
文摘Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.
基金supported by the National Natural Science Foundation of China(61502522).
文摘Separation and recognition of radar signals is the key function of modern radar reconnaissance,which is of great sig-nificance for electronic countermeasures and anti-countermea-sures.In order to improve the ability of separating mixed signals in complex electromagnetic environment,a blind source separa-tion algorithm based on degree of cyclostationarity(DCS)crite-rion is constructed in this paper.Firstly,the DCS criterion is con-structed by using the cyclic spectrum theory.Then the algo-rithm flow of blind source separation is designed based on DCS criterion.At the same time,Givens matrix is constructed to make the blind source separation algorithm suitable for multiple sig-nals with different cyclostationary frequencies.The feasibility of this method is further proved.The theoretical and simulation results show that the algorithm can effectively separate and re-cognize common multi-radar signals.
基金Project(cstc2020jcyj-bshX0106)supported by the Chongqing Postdoctoral Science Foundation,ChinaProject(2020M683247)supported by the China Postdoctoral Science Foundation+1 种基金Project(cstc2020jcyj-zdxmX0023)supported by the Key Natural Science Foundation Project of Chongqing,ChinaProject(551974043)supported by the National Natural Science Foundation of China。
文摘Source location is the core foundation of microseismic monitoring.To date,commonly used location methods have usually been based on the ray-tracing travel-time technique,which generally adopts an L1 or L2 norm to establish the location objective function.However,the L1 norm usually achieves low location accuracy,whereas the L2 norm is easily affected by large P-wave arrival-time picking errors.In addition,traditional location methods may be affected by the initial iteration point used to find a local optimum location.Furthermore,the P-wave arrival-time data that have travelled long distances are usually poor in quality.To address these problems,this paper presents a microseismic source location method using the Log-Cosh function and distant sensor-removed P-wave arrival data.Its basic principles are as follows:First,the source location objective function is established using the Log-Cosh function.This function has the stability of the L1 norm and location accuracy of the L2 norm.Then,multiple initial points are generated randomly in the mining area,and the established Log-Cosh location objective function is used to obtain multiple corresponding location results.The average value of the 50 location points with the largest data field potential values is treated as the initial location result.Next,the P-wave travel times from the initial location result to triggered sensors are calculated,and then the P-wave arrival data with travel times exceeding 0.2 s are removed.Finally,the aforementioned location steps are repeated with the denoised P-wave arrival dataset to obtain a high-precision location result.Two synthetic events and eight blasting events from the Yongshaba mine,China,were used to test the proposed method.Regardless of whether the P-wave arrival data with long travel times were eliminated,the location error of the proposed method was smaller than that of the L1/L2 norm and trigger-time-based location method(TT1/TT2 method).Furthermore,after eliminating the Pwave arrival data with long travel distances,the location accuracy of these three location methods increased,indicating that the proposed location method has good application prospects.
文摘A new method based on phase difference analysis is proposed for the single-channel mixed signal separation of single-channel radar fuze.This method is used to estimate the mixing coefficients of de-noised signals through the cumulants of mixed signals,solve the candidate data set by the mixing coefficients and signal analytical form,and resolve the problem of vector ambiguity by analyzing the phase differences.The signal separation is realized by exchanging data of the solutions.The waveform similarity coefficients are calculated,and the time鈥攆requency distributions of separated signals are analyzed.The results show that the proposed method is effective.
基金Project(2006BAK04B03) supported by the National Basic Research Program of ChinaProject(CX2009B053) supported by Innovation Foundation for Postgraduate Students of Hunan Province,ChinaProject(2009ybfz08) supported by the Doctoral Dissertation of Central South University,China
文摘in order to achieve a more efficient way to accurately detect the position of the fire source of spontaneous combustion underground mine, a simple fire source locating method, based on infrared scanning system which can determine the point where the highest temperature on the surface of igniting ores occurs, was proposed. First, the differential equations that describe heat flow in ore body were presented and the relationship between the surface temperature distribution and the depth and intensity of inner fire source was established with a relatively simple heat transfer model. With the solution of equation, the expression of the relationship between the surface temperature distribution and the inner fire source was deduced and the mathematical-physical model of heat transfer process was set up. Then, with the model, visualization of fire source on the basis of MATLAB simulation platform was realized. The results show that： 1） within 10 m, when the detecting depth is less than 2 m, the temperature perturbation on ores surface can change rapidly, and then slowly; after 4 m, in contrast, it changes very little, and is even close to zero at 10 m; 2） When it is close to self-ignition duration and the detective depths are 2, 5 and 10 m, respectively, the maximum temperature differences are correspondingly 0.5, 0.04 and 0.005 ℃ in the scope of 1 m×1 m; under the same condition, the maximum temperature differences are 1.391, 0.136 and 0.018 ℃, respectively, in the scope of 2 m×2 m. Therefore, this system can be used to measure the temperature differences on the surface of ore body and determine the highest temperature point directly. Also, it is possible to determine the depth of fire source and its intensity by locating method of fire source indirectly.
基金Project(KYCX17_0500)supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province,ChinaProjects(2013/B17020664X,2014B17614)supported by the Fundamental Research Funds for the Central Universities,China+2 种基金Project(41174043)supported by the National Natural Science Foundation of ChinaProject supported by the Funds from China Scholarship Council(CSC)Project(487237)supported by the NSERC Discovery Grant for LIU Qin-ya。
文摘We have developed a type of L-shaped single-component geophone array as a single station(L-array station)for surface microseismic monitoring.The L-array station consists of two orthogonal sensor arrays,each being a linear array of single-component sensors.L-array stations can be used to accurately estimate the polarization of first arrivals without amplitude picking.In a synthetic example,we first use segmentally iterative ray tracing(SIRT)method and forward model to calculate the travel time and polarization of first arrivals at a set of L-array stations.Then,for each L-array station,the relative delay times of first arrivals along sensor arrays are used to estimate the polarization vector.The small errors in estimated polarization vectors show the reliability and robustness of polarization estimation based on L-array stations.We then use reverse-time ray-tracing(RTRT)method to locate the source position based on estimated polarizations at a set of L-array stations.Very small errors in inverted source location and origin time indicate the great potential of L-array stations for source localization applications in surface microseismic monitoring.
基金supported by the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space(KF20202109)the National Natural Science Foundation of China(82004259)the Young Talent Training Project of Guangzhou University of Chinese Medicine(QNYC20190110).
文摘Most of the near-field source localization methods are developed with the approximated signal model,because the phases of the received near-field signal are highly non-linear.Nevertheless,the approximated signal model based methods suffer from model mismatch and performance degradation while the exact signal model based estimation methods usually involve parameter searching or multiple decomposition procedures.In this paper,a search-free near-field source localization method is proposed with the exact signal model.Firstly,the approximative estimates of the direction of arrival(DOA)and range are obtained by using the approximated signal model based method through parameter separation and polynomial rooting operations.Then,the approximative estimates are corrected with the exact signal model according to the exact expressions of phase difference in near-field observations.The proposed method avoids spectral searching and parameter pairing and has enhanced estimation performance.Numerical simulations are provided to demonstrate the effectiveness of the proposed method.
文摘Analyzed the relation between time delay difference and time delay estimation errors, based on the principles of three-point locating, a reformed threshold method for time delay difference estimation of impulse signals, called as amendment estimation for short, is developed by introducing channel equalization technique to its conventional version, named as direct estimation in this paper, to improve the estimation stability. After inherent relationship between time delay and phase shift of signals is analyzed, an integer period error compensation method utilized the diversities of both contribution share and contribution mode of concerned estimates is proposed under the condition of high precision phase lag estimation. Finally, a cooperative multi-threshold estimation method composed of amendment and direct estimations to process impulse signals with three thresholds is established. In sea trials data tests of passive locating, this method improves the estimation precision of time delay difference efficiently. The experiments verify the theoretical predictions.
基金supported by the Major National Science&Technology Projects(2010ZX03006-002-04)the National Natural Science Foundation of China(61072070)+4 种基金the Doctorial Programs Foundation of the Ministry of Education(20110203110011)the"111 Project"(B08038)the Fundamental Research Funds of the Ministry of Education(72124338)the Key Programs for Natural Science Foundation of Shanxi Province(2012JZ8002)the Foundation of State Key Laboratory of Integrated Services Networks(ISN1101002)
文摘With the emergence of location-based applications in various fields, the higher accuracy of positioning is demanded. By utilizing the time differences of arrival （TDOAs） and gain ratios of arrival （GROAs）, an efficient algorithm for estimating the position is proposed, which exploits the Broyden-Fletcher-Goldfarb-Shanno （BFGS） quasi-Newton method to solve nonlinear equations at the source location under the additive measurement error. Although the accuracy of two-step weighted-least-square （WLS） method based on TDOAs and GROAs is very high, this method has a high computational complexity. While the proposed approach can achieve the same accuracy and bias with the lower computational complexity when the signal-to-noise ratio （SNR） is high, especially it can achieve better accuracy and smaller bias at a lower SNR. The proposed algorithm can be applied to the actual environment due to its real-time property and good robust performance. Simulation results show that with a good initial guess to begin with, the proposed estimator converges to the true solution and achieves the Cramer-Rao lower bound （CRLB） accuracy for both near-field and far-field sources.
基金supported by the National Natural Science Foundation of China(61501142)the China Postdoctoral Science Foundation(2015M571414)+3 种基金the Fundamental Research Funds for the Central Universities(HIT.NSRIF.2016102)Shandong Provincial Natural Science Foundation(ZR2014FQ003)the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology(HIT.NSRIF 2013130HIT(WH)XBQD 201022)
文摘In most literature about joint direction of arrival（DOA） and polarization estimation, the case that sources possess different power levels is seldom discussed. However, this case exists widely in practical applications, especially in passive radar systems. In this paper, we propose a joint DOA and polarization estimation method for unequal power sources based on the reconstructed noise subspace. The invariance property of noise subspace（IPNS） to power of sources has been proved an effective method to estimate DOA of unequal power sources. We develop the IPNS method for joint DOA and polarization estimation based on a dual polarized array. Moreover, we propose an improved IPNS method based on the reconstructed noise subspace, which has higher resolution probability than the IPNS method. It is theoretically proved that the IPNS to power of sources is still valid when the eigenvalues of the noise subspace are changed artificially. Simulation results show that the resolution probability of the proposed method is enhanced compared with the methods based on the IPNS and the polarimetric multiple signal classification（MUSIC） method. Meanwhile, the proposed method has approximately the same estimation accuracy as the IPNS method for the weak source.
