联合多站阵元域数据的水下目标检测与跟踪
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摘要
为了提高复杂海洋环境中目标的检测、跟踪性能,提出一种联合多站阵元域数据的水下目标检测与跟踪方法.该方法采用序列马尔科夫链蒙特卡洛思想对目标进行采样更新,通过对接收概率中的后验概率以及采样函数进行分解展开,并根据多站阵元域数据计算采样粒子的联合似然,在迭代过程中实现目标数目和目标状态的联合估计.研究结果表明,该方法对单目标的平均定位误差在较高信噪比下能够稳定在50 m以内,对多目标随机出入场景中新生及消失目标实现有效检测,同时对强干扰下弱目标及交叉目标实现有效检测跟踪。仿真结果和海试数据均验证该方法具有良好的目标检测与跟踪性能。
An algorithm of underwater target detection and tracking based on array element domain data from multiarrays is presented in order to improve the target detection and tracking ability in the complex marine environment.Sequential Markov chain Monte Carlo method is used to sample and update the target parameters.By decomposing the posterior probability and sampling function in the received likelihood ratio,and calculating the joint likelihood function of the sampled particles according to the multi-array element domain data,a joint estimate of the target number and states is achieved during the iterative process.The research results show that the average positioning error of the single target can be stabilized within 50 m at a high SNR,the new and vanishing targets can be effectively detected under the situation of multiple targets going in and out randomly,and both the weak targets and crosses targets can achieve effective detection and tracking.The simulation and Sea trial results show that the algorithm is able to detect and track the targets functionally.
An algorithm of underwater target detection and tracking based on array element domain data from multiarrays is presented in order to improve the target detection and tracking ability in the complex marine environment.Sequential Markov chain Monte Carlo method is used to sample and update the target parameters.By decomposing the posterior probability and sampling function in the received likelihood ratio,and calculating the joint likelihood function of the sampled particles according to the multi-array element domain data,a joint estimate of the target number and states is achieved during the iterative process.The research results show that the average positioning error of the single target can be stabilized within 50 m at a high SNR,the new and vanishing targets can be effectively detected under the situation of multiple targets going in and out randomly,and both the weak targets and crosses targets can achieve effective detection and tracking.The simulation and Sea trial results show that the algorithm is able to detect and track the targets functionally.
引文
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17 Wax M,Ziskind I.Detection of the number of coherent signals by the MDL principle.IEEE Trans.Acoust.Speech Signal Process.,1989; 37(8):1190-1196
18张杰,廖桂生,王珏.对角加载对信号源数检测性能的改善.电子学报,2004; 32(12):2098—2101
2相明,王昭,李宏,赵俊渭,宫先仪.水声信号数据融合系统的性能研究.声学学报,1999; 24(6):574-581
3童伟峰,吴国清.一种多传感器目标跟踪的数据融合方法.声学学报,2003; 28(5):416—420
4曹利,李宇,黄勇.基于修正时延粒子滤波的水声传感器网络目标跟踪.声学技术,2012; 31(1):67-71
5许兆鹏,韩树平.一种多基阵机动目标被动跟踪算法.应用声学,2011; 30(4):282—287
6 Sidi A J,Weiss A J.Tracking of a moving emitter based on delay and Doppler shift using a particle filter.IEEE Convention of Electrical&Electronics Engineers in Israel,IEEE.2010
7 WEISS A J.Direct position determination of narrowband radio frequency transmitters.IEEE Signal Process.Lett.,2004; 11(5):513—516
8 WANG Zhong,CHEN Fuhu.A unified algorithm for target detection and tracking based on data of array sensors.Chinese Journal of Acoustics,2008; 27(3):281—288
9 Xu L,Liu C,Yi W et al.A particle filter based trackbefore-detect procedure for towed passive array sonar system.2017 IEEE Radar Conference(RadarConfl7),IEEE,2017
10 Kreucher C M,Shapo B,Bethel R.Multitarget detection and tracking using multi-sensor passive acoustic data.In:IEEE Aerospace Conference Proceedings,IEEE,2009
11 Septier F,Pang S K,Carmi A et al.On MCMC-Based particle methods for Bayesian filtering:Application to multitarget tracking.IEEE International Workshop on Computational Advances in Multi-sensor Adaptive Processing,2009
12 Septier F,Peters G W.Langevin and hamiltonian based sequential MCMC for efficient bayesian filtering in highdimensional spaces.IEEE J.Sel.Top.Signal Process.,2016; 10(2):312—327
13侯云山,黄建国,张立杰等.一种新的浅海目标方位估计方法.西安交通大学学报,2008; 42(10):1295-1299
14朱光明.异步水下传感器网络目标跟踪算法研究.浙江大学,2015
15金美娜,赵拥军,盖江伟.一种基于混合RJMCMC方法的宽带信号DOA估计方法.电子与信息学报,2010; 32(2)
16 Pang S K,Li J,Godsill S J.Models and algorithms for detection and tracking of coordinated groups.In:IEEE Aerospace Conference Proceedings,2008:1—17
17 Wax M,Ziskind I.Detection of the number of coherent signals by the MDL principle.IEEE Trans.Acoust.Speech Signal Process.,1989; 37(8):1190-1196
18张杰,廖桂生,王珏.对角加载对信号源数检测性能的改善.电子学报,2004; 32(12):2098—2101