一种利用MIMO雷达的CWLS目标定位算法
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摘要
针对分布式多进多出雷达,提出了一种基于时延测量值的约束加权最小二乘定位算法。该方法通过引入目标到参考站的距离这一变量,将目标定位方程进行了伪线性化处理,并构建出代价函数;随后,进一步挖掘出该变量与目标位置的关系,并将其作为约束条件;最后,将非线性的目标定位问题转化为带二次约束的二次规划问题,通过采用拉格朗日乘子算法求得目标定位的闭合解。仿真结果表明,所提出的算法在相对较高噪声的情况下仍然能够达到克拉美罗界,具有较强的抗噪性。
For the separated MIMO radar system,a constrained weighted least squares algorithm is proposed by using time delay measurements.By introducing the variable which is the distance between the target and the reference station,the target location equation is pseudolinearized and the cost function is derived.And then,by further study,the relationship between the variable and the target position is explored and used as the constraint condition.Finally,the problem of locating the target is transformed from the nonlinear equation into the quadratic program problems with quadratic constraints,and by use of the Lagrange multiplier method,the target position is solved in a closed-form.Simulation results verify that the proposed algorithm can attain the Cramer-Rao Lower Bound in a relatively high level of noise and that it is robust.
For the separated MIMO radar system,a constrained weighted least squares algorithm is proposed by using time delay measurements.By introducing the variable which is the distance between the target and the reference station,the target location equation is pseudolinearized and the cost function is derived.And then,by further study,the relationship between the variable and the target position is explored and used as the constraint condition.Finally,the problem of locating the target is transformed from the nonlinear equation into the quadratic program problems with quadratic constraints,and by use of the Lagrange multiplier method,the target position is solved in a closed-form.Simulation results verify that the proposed algorithm can attain the Cramer-Rao Lower Bound in a relatively high level of noise and that it is robust.
引文
[1]AMIRI R,ZAMANI H,BEHNIA F,et al.Sparsity-aware Target Localization Using TDOA/AOA Measurements in Distributed MIMO Radars[J].ICT Express,2016,2(1):23-27.
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[7]AMIRI R,BEHNIA F.An Efficient Weighted Least Squares Estimator for Elliptic Localization in Distributed MIMORadars[J].IEEE Signal Processing Letters,2017,24(6):902-906.
[8]GODRICH H,HAIMOVICH A M,BLUM R S.Target Localization Accuracy Gain in MIMO Radar-based Systems[J].IEEE Transactions on Information Theory,2010,56(6):2783-2803.
[9]DIANAT M,TABAN M R,DIANAT J,et al.Target Localization Using Least Squares Estimation for MIMO Radars with Widely Separated Antennas[J].IEEE Transactions on Aerospace and Electronic Systems,2013,49(4):2730-2741.
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[11]DU Y,WEI P.An Explicit Solution for Target Localization in Noncoherent Distributed MIMO Radar Systems[J].IEEESignal Processing Letters,2014,21(9):1093-1097.
[12]李明强,郭田德,韩丛英.等式约束二次规划问题的新的梯度投影算法(英文)[J].中国科学院大学学报,2018,35(3):289-296.LI Mingqiang,GUO Tiande,HAN Congying.New Project Gradient Methods for Quadratic Programming with Linear Equality Constraints[J].Journal of University of Chinese Academy of Sciences,2018,35(3):289-296.
[13]YU H G,HUANG G M,GAO J,et al.Practical Constrained Least-square Algorithm for Moving Source Location Using TDOA and FDOA Measurements[J].Journal of Systems Engineering and Electronics,2012,23(4):488-494.
[14]HE Q,BLUM R S,HAIMOVICH A M.Noncoherent MIMO Radar for Location and Velocity Estimation:More Antennas Means Better Performance[J].IEEE Transactions on Signal Processing,2010,58(7):3661-3680.
[2]项喆,陈伯孝,杨明磊.频率分集雷达最优频率间隔选择方法[J].西安电子科技大学学报,2017,44(4):12-17.XIANG Zhe,CHEN Baixiao,YANG Minglei.Frequency Increment Optimization Method for Frequency Diverse Radar[J].Journal of Xidian University,2017,44(4):12-17.
[3]LIANG J,LEUNG C S,SO H C.Lagrange Programming Neural Network Approach for Target Localization in Distributed MIMO Radar[J].IEEE Transactions on Signal Processing,2016,64(6):1574-1585.
[4]LI W C,TANG Q,HUANG C F,et al.Location Algorithms for Moving Target in Non-coherent Distributed Multipleinput Multiple-output Radar Systems[J].IET Signal Processing,2017,11(5):504-514.
[5]AMIRI R,BEHNIA F,MALEKI SADR M A.Positioning in MIMO Radars Based on Constrained Least Squares Estimation[J].IEEE Communications Letters,2017,21(10):2222-2225.
[6]ZAMANI H,AMIRI R,BEHNIA F.Compressive Sensing for Elliptic Localization in MIMO Radars[C]//Proceedings of the 2016 24th Iranian Conference on Electrical Engineering.Piscataway:IEEE,2016:525-528.
[7]AMIRI R,BEHNIA F.An Efficient Weighted Least Squares Estimator for Elliptic Localization in Distributed MIMORadars[J].IEEE Signal Processing Letters,2017,24(6):902-906.
[8]GODRICH H,HAIMOVICH A M,BLUM R S.Target Localization Accuracy Gain in MIMO Radar-based Systems[J].IEEE Transactions on Information Theory,2010,56(6):2783-2803.
[9]DIANAT M,TABAN M R,DIANAT J,et al.Target Localization Using Least Squares Estimation for MIMO Radars with Widely Separated Antennas[J].IEEE Transactions on Aerospace and Electronic Systems,2013,49(4):2730-2741.
[10]KAY S M.Fundamentals of Statistical Signal Processing:Estimation Theory[M].New Jork:Prentice-Hall,1993:20-30.
[11]DU Y,WEI P.An Explicit Solution for Target Localization in Noncoherent Distributed MIMO Radar Systems[J].IEEESignal Processing Letters,2014,21(9):1093-1097.
[12]李明强,郭田德,韩丛英.等式约束二次规划问题的新的梯度投影算法(英文)[J].中国科学院大学学报,2018,35(3):289-296.LI Mingqiang,GUO Tiande,HAN Congying.New Project Gradient Methods for Quadratic Programming with Linear Equality Constraints[J].Journal of University of Chinese Academy of Sciences,2018,35(3):289-296.
[13]YU H G,HUANG G M,GAO J,et al.Practical Constrained Least-square Algorithm for Moving Source Location Using TDOA and FDOA Measurements[J].Journal of Systems Engineering and Electronics,2012,23(4):488-494.
[14]HE Q,BLUM R S,HAIMOVICH A M.Noncoherent MIMO Radar for Location and Velocity Estimation:More Antennas Means Better Performance[J].IEEE Transactions on Signal Processing,2010,58(7):3661-3680.