基于滤波器网格失配的分布式相参雷达目标参数估计方法
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摘要
针对分布式相参雷达(distributed coherent aperture radar,DCAR)精确的目标参数估计问题,首先建立了以多普勒分复用(Doppler division multiple access,DDMA)波形作为发射波形、存在滤波器网格失配的DCAR信号模型,接着分析并验证了滤波器网格失配严重影响目标参数估计进而降低DCAR信号相参合成性能,最后提出了联合全局-局域搜索和基于稀疏傅里叶变换(sparse Fourier transform,SFT)的两种DCAR目标参数估计方法来降低滤波器网格失配,联合全局-局域搜索的方法通过对滤波器局域加密的方式降低网格失配。为了降低运算量,利用目标信号频率相对于整体频域是稀疏的特性,采用基于SFT搜索的方法通过梯度下降的方式避免滤波器的遍历搜索。仿真实验验证了所提方法的有效性。
For the problem of accurate target parameter estimation in distributed coherent aperture radar(DCAR),a DCAR signal model,which takes the Doppler division multiple access(DDMA)waveform as the transmitting waveform and the grid mismatch filtering into consideration,is firstly established.Then the detrimental effects on the target parameter estimation caused by grid mismatch filtering are analyzed and validated,the results of which would decrease DCAR signal coherence-synthetic performance.Finally,two DCAR target parameter estimation methods based on joint global-local search and sparse Fourier transform(SFT)are proposed,respectively.The joint global-local search method weakens the grid mismatch effects by means of setting refined filters locally.To reduce the computation burden,taking advantages of the characteristic that target frequencies are sparse relative to the whole frequency domain,the search method based on SFT is employed,which avoids the traversal search of filters by the gradient descent method.The effectiveness of proposed method is verified by the simulation experiments.
For the problem of accurate target parameter estimation in distributed coherent aperture radar(DCAR),a DCAR signal model,which takes the Doppler division multiple access(DDMA)waveform as the transmitting waveform and the grid mismatch filtering into consideration,is firstly established.Then the detrimental effects on the target parameter estimation caused by grid mismatch filtering are analyzed and validated,the results of which would decrease DCAR signal coherence-synthetic performance.Finally,two DCAR target parameter estimation methods based on joint global-local search and sparse Fourier transform(SFT)are proposed,respectively.The joint global-local search method weakens the grid mismatch effects by means of setting refined filters locally.To reduce the computation burden,taking advantages of the characteristic that target frequencies are sparse relative to the whole frequency domain,the search method based on SFT is employed,which avoids the traversal search of filters by the gradient descent method.The effectiveness of proposed method is verified by the simulation experiments.
引文
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[24]MUDUMBAI R,BROWN D R,MADHOW U,et al.Distributed transmit beamforming:challenges and recent progress[J].IEEE Communications Magazine,2009,47(2):102-110.
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[26]SHEN Q,LIU W,WANG L,et al.Adaptive beamforming for target detection and surveillance based on distributed unmanned aerial vehicle platforms[J].IEEE Access,2018,6:60812-60823.
[27]FAN Y,ZHOU Y,HE D,et al.Fast transmit beamforming with distributed antennas[J].IEEE Antennas and Wireless Propagation Letters,2016,16:121-124.
[28]YANG X P,YIN P L,ZENG T.Time and phase synchronization for wideband distributed coherent aperture radar[C]∥Proc.of the International Radar Conference,2013.
[29]CHATTERJEE P,NANZER J A.Effects of time alignment errors in coherent distributed radar[C]∥Proc.of the IEEE Radar Conference,2018.
[30]SHI L,HASSANIEH H,DAVIS A,et al.Light field reconstruction using sparsity in the continuous Fourier domain[J].ACM Trans.on Graphics,2014,34(1):1-13.
[31]GILBERT A C,INDYK P,IWEN M,et al.Recent developments in the sparse Fourier transform:a compressed Fourier transform for big data[J].IEEE Signal Processing Magazine,2014,31(5):91-100.
[32]WANG S G,PETAL V M,PETROPULU A.A robust sparse Fourier transform and its application in radar signal processing[J].IEEE Trans.on Aerospace and Electronic Systems,2017,53(6):2735-2755.
[33]FORSYTHE K W,BLISS D W.MIMO radar waveform constraints for GMTI[J].IEEE Journal of Selected Topics in Signal Processing,2010,4(1):21-32.
[34]RABIDEAU D J.MIMO radar waveforms and cancellation ratio[J].IEEE Trans.on Aerospace and Electronic Systems,2012,48(2):1167-1178.
[35]ROSSUM W V,ANITORI L.Doppler ambiguity resolution using random slow-time code division multiple access MIMO radar with sparse signal processing[C]∥Proc.of the IEEE Radar Conference,2018.
[2]CUOMO K M,COUTTS S D,MCHARG J C,et al.Wideband aperture coherence processing for next generation radar(NexGen)[R].MIT Lincoln Laboratory,2004.
[3]FLETCHER A S,ROBEY F C.Performance bounds for adaptive coherence of sparse array radar[C]∥Proc.of the 11th Conference Adaptive Sensors Array Processing,2003:290-293.
[4]SUN P L,TANG J,HE Q,et al.Cramer-Rao bound of parameters estimation and coherence performance for next generation radar[J].IET Radar,Sonar and Navigation,2013,7(5):553-567.
[5]TANG X W,TANG J,HE Q,et al.Cramer-Rao bounds and coherence performance analysis for next generation radar with pulse trains[J].Sensors,2013,13(4):5347-5367.
[6]ZENG T,YIN P L,LIU Q H.Wideband distributed coherent aperture radar based on stepped frequency signal:theory and experimental results[J].IET Radar Sonar and Navigation,2016,10(4):672-688.
[7]ULRICH M,YANG B.Multi-carrier MIMO radar:a concept of sparse array for improved DOA estimation[C]∥Proc.of the Radar Conference,2016.
[8]LEE J H,LEE J H,WOO J M.Method for obtaining three-and four-element array spacing for interferometer direction-finding system[J].IEEE Antennas and Wireless Propagation Letters,2016,15:897-900.
[9]LIU Z M,GUO F C.Azimuth and elevation estimation with rotating long-baseline interferometers[J].IEEE Trans.on Signal Processing,2015,63(9):2405-2419.
[10]LONG T,ZHANG H G,ZENG T,et al.High accuracy unambiguous angle estimation using multi-scale combination in distributed coherent aperture radar[J].IET Radar,Sonar and Navigation,2017,11(7):1090-1098.
[11]鲁耀兵，高红卫．分布相参雷达[M]．北京：国防工业出版社，2017.LU Y B,GAO H W.Distributed aperture radar[M].Beijing:National Defense Industry Press,2017.
[12]NANZER J A,SCHMID R L,COMBERIATE T M,et al.Open-loop coherent distributed arrays[J].IEEE Trans.on Microwave Theory and Techniques,2017,65(5):1-11.
[13]刘兴华，徐振海，肖顺平．分布式相参雷达几何布置约束条件[J]．系统工程与电子技术，2017,39(8):1723-1731.LIU X H,XU Z H,XIAO S P.Geometric arrangement constraints of distributed coherent aperture radar[J].Systems Engineering and Electronics,2017,39(8):1723-1731.
[14]周宝亮，高红卫，文树梁，等．分布式相参雷达基线选择与标定误差分析[J]．系统工程与电子技术，2018,40(11):2438-2443.ZHOU B L,GAO H W,WEN S L,et al.Distributed coherent radar baseline selection and calibration error analysis[J].Systems Engineering and Electronics,2018,40(11):2438-2443.
[15]YANG S Q,YU X X,KONG L J,et al.Coherent unambiguous transmit for sparse linear array with geography constraint[J].IET Radar,Sonar and Navigation,2017,11(2):386-393.
[16]YANG Y C,YI W,ZHANG T X,et al.Fast optimal antenna placement for distributed MIMO radar with surveillance performance[J].IEEE Signal Processing Letters,2015,22(11):1955-1959.
[17]ELISSION S M,NANZER J A.Comparison of crossover recombination operators in GA-optimized sparse linear array design[C]∥Proc.of the IEEE International Symposium on Antennas and Propagation,2017:145-146.
[18]LIU X H,XU Z H,XIAO S P.Performance gain bounds of coherently combining multiple radars in a target-based calibration manner[J].Journal of Systems Engineering and Electronics,2019,30(2):278-287.
[19]LIU X H,XU Z H,WANG L S B,et al.Performance analysis of coherent parameters estimation algorithm for distributed coherent aperture radar[C]∥Proc.of the IEEE International Conference on Signal Processing,Communications and Computing,2017:1-5.
[20]GAO H W,ZHOU B L,ZHOU D M,et al.Performance analysis and experimental study on distributed aperture coherence-synthetic radar[C]∥Proc.of the CIE International Conference on Radar,2016:343-347.
[21]刘兴华，徐振海，王罗胜斌，等．基于信号重建的分布式相参雷达相参参数估计算法[J]．系统工程与电子技术，2018,40(9):1931-1938.LIU X H,XU Z H,WANG L S B,et al.Coherent parameters estimation algorithm for distributed coherent aperture radar based on signal reconstruction[J].Systems Engineering and Electronics,2018,40(9):1931-1938.
[22]LIU X H,XU Z H,LIU X,et al.A clean signal reconstruction approach for coherently combining multiple radars[J].EURASIP Journal on Advances in Signal Processing,2018,2018(1):47-57.
[23]LIU X H,XU Z H,WANG L S B,et al.Dual-radar coherently combining:generalized paradigm and verification example[J].IET Radar,Sonar and Navigation,2019,13(5):689-699.
[24]MUDUMBAI R,BROWN D R,MADHOW U,et al.Distributed transmit beamforming:challenges and recent progress[J].IEEE Communications Magazine,2009,47(2):102-110.
[25]LU Y,FANG J,GUO Z,et al.Distributed transmit beamforming for UAV to base communications[J].China Communications,2019(1):15-25.
[26]SHEN Q,LIU W,WANG L,et al.Adaptive beamforming for target detection and surveillance based on distributed unmanned aerial vehicle platforms[J].IEEE Access,2018,6:60812-60823.
[27]FAN Y,ZHOU Y,HE D,et al.Fast transmit beamforming with distributed antennas[J].IEEE Antennas and Wireless Propagation Letters,2016,16:121-124.
[28]YANG X P,YIN P L,ZENG T.Time and phase synchronization for wideband distributed coherent aperture radar[C]∥Proc.of the International Radar Conference,2013.
[29]CHATTERJEE P,NANZER J A.Effects of time alignment errors in coherent distributed radar[C]∥Proc.of the IEEE Radar Conference,2018.
[30]SHI L,HASSANIEH H,DAVIS A,et al.Light field reconstruction using sparsity in the continuous Fourier domain[J].ACM Trans.on Graphics,2014,34(1):1-13.
[31]GILBERT A C,INDYK P,IWEN M,et al.Recent developments in the sparse Fourier transform:a compressed Fourier transform for big data[J].IEEE Signal Processing Magazine,2014,31(5):91-100.
[32]WANG S G,PETAL V M,PETROPULU A.A robust sparse Fourier transform and its application in radar signal processing[J].IEEE Trans.on Aerospace and Electronic Systems,2017,53(6):2735-2755.
[33]FORSYTHE K W,BLISS D W.MIMO radar waveform constraints for GMTI[J].IEEE Journal of Selected Topics in Signal Processing,2010,4(1):21-32.
[34]RABIDEAU D J.MIMO radar waveforms and cancellation ratio[J].IEEE Trans.on Aerospace and Electronic Systems,2012,48(2):1167-1178.
[35]ROSSUM W V,ANITORI L.Doppler ambiguity resolution using random slow-time code division multiple access MIMO radar with sparse signal processing[C]∥Proc.of the IEEE Radar Conference,2018.