应用膨胀算法提取目标的直接定位算法
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摘要
为了解决被动雷达系统中的多发射源定位问题,提出了一种基于多重信号分类(MUSIC)算法和图像膨胀(IE)算法的直接定位方法。该方法结合了谱分析中的MUSIC思想,通过对接收量测协方差矩阵进行特征分析求解目标的位置。首先,在目标个数未知的前提下,利用Akaike信息准则(AIC)来确定模型阶数;然后,推导了基于MUSIC的定位代价函数;之后,利用图像膨胀算法处理得到的代价函数平面;最后,膨胀处理后的输出为目标个数及目标位置的估计值。提出的算法有效地解决了目标检测及提取的问题,能够确定多个目标的位置坐标,为后续的定位性能分析提供可能性,也保证了算法的完整性。进一步地分析了多个临近目标情况下影响目标提取性能的主要因素。
In order to solve the problem of localizing multiple transmitters in passive radar system,a direct position determination method based on the multiple signal classification(MUSIC)algorithm and the image expansion(IE)algorithm is proposed.This method combines the idea of MUSIC in spectral analysis and determines the positions of targets by performing feature analysis on the measured covariance matrix of the received signal.First,under the premise of the unknown number of the targets,the Akaike information criteria(AIC)is used to determine the order of the model.Then,the cost function for localization is deduced based on MUSIC.Afterwards,the IE algorithm is used to deal with the cost function plane.Finally,the outputs of the expansion processing are the estimated number and positions of targets.The proposed approach effectively solves the problem of target detection and extraction and can accurately locate multiple targets,which makes it possible to do the subsequent performance analysis and also ensure the completeness of the algorithm.Moreover,we analyze the main factors that affect the target extraction performance in the case where there are multiple adjacent targets.
In order to solve the problem of localizing multiple transmitters in passive radar system,a direct position determination method based on the multiple signal classification(MUSIC)algorithm and the image expansion(IE)algorithm is proposed.This method combines the idea of MUSIC in spectral analysis and determines the positions of targets by performing feature analysis on the measured covariance matrix of the received signal.First,under the premise of the unknown number of the targets,the Akaike information criteria(AIC)is used to determine the order of the model.Then,the cost function for localization is deduced based on MUSIC.Afterwards,the IE algorithm is used to deal with the cost function plane.Finally,the outputs of the expansion processing are the estimated number and positions of targets.The proposed approach effectively solves the problem of target detection and extraction and can accurately locate multiple targets,which makes it possible to do the subsequent performance analysis and also ensure the completeness of the algorithm.Moreover,we analyze the main factors that affect the target extraction performance in the case where there are multiple adjacent targets.
引文
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[2]朱新权,俞志强,蒋晓宇,等.时差定位无源雷达探测威力量化分析研究[J].雷达科学与技术,2015,13(1):55-59.ZHU Xinquan,YU Zhiqiang,JIANG Xiaoyu,et al.Quantitative Analysis of TDOA Passive Radar Detection Coverage[J].Radar Science and Technology,2015,13(1):55-59.(in Chinese)
[3]苏峰,王昌海,徐征.基于最小二乘的时差定位算法[J].雷达科学与技术,2013,11(6):621-625.SU Feng,WANG Changhai,XU Zheng.TDOA Location Algorithms Based on the Least Squares[J].Radar Science and Technology,2013,11(6):621-625.(in Chinese)
[4]WEISS A J.Direct Position Determination of Narrowband Radio Frequency Transmitters[J].IEEE Signal Processing Letters,2004,11(5):513-516.
[5]WEISS A J,AMAR A.Direct Position Determination of Multiple Radio Signals[J].EURASIP Journal on Advances in Signal Processing,2005,2005:653549.
[6]TIRER T,WEISS A J.High Resolution Direct Position Determination of Radio Frequency Sources[J].IEEESignal Processing Letters,2016,23(2):192-196.
[7]SCHMIDT R.Multiple Emitter Location and Signal Parameter Estimation[J].IEEE Trans on Antennas and Propagation,1986,34(3):276-280.
[8]YI Wei,CHEN Zhenhua,HOSEINNEZHAD R,et al.Joint Estimation of Location and Signal Parameters for an LFM Emitter[J].Signal Processing,2017,134:100-112.
[9]SCHULTZ R R,STEVENSON R L.Improved Definition Image Expansion[C]∥IEEE International Conference on Acoustics,Speech,and Signal Processing,San Francisco,CA:IEEE,1992:173-176.
[10]邓仕超,黄寅.二值图像膨胀腐蚀的快速算法[J].计算机工程与应用,2017,53(5):207-211.
[11]VAN TREES H L.Optimum Array Processing:Part IV of Estimation,Modulation Theory[M].New York:John Wiley and Sons Inc,2002:293-303.
[12]何子述,夏威.现代数字信号处理及其应用[M].北京:清华大学出版社,2009.
[13]WAX M,KAILATH T.Detection of Signals by Information Theoretic Criteria[J].IEEE Trans on Acoustics Speech and Signal Processing,1985,33(2):387-392.