基于分块粒子滤波的多节点协同无源探测解算算法  

Passive Location Algorithm of Multiple-Node Based on Distributed Particle Filter

作　　者：惠洋 唐铂 罗德巳 杨小龙 HUI Yang;TANG Bo;LUO Desi;YANG Xiaolong(Southwest China Research Institute of Electronic Equipment,Chengdu 610036,China;School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]中国电子科技集团公司第二十九研究所,成都610036 [2]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《电子信息对抗技术》2023年第6期61-67,共7页Electronic Information Warfare Technology

基　　金：重庆市自然科学基金项目(cstc2019jcyj-msxmX0635)。

摘　　要：多节点协同无源探测是实现对机动雷达快速定位的有效手段。在空间上分离的多个节点同时无源侦察雷达信号,获取信号到达不同节点的到达时间差(Time Difference of Arrival,TDOA)和频率差(Frequency Difference of Arrival,FDOA)。通过TDOA/FDOA联合解算,完成对目标雷达位置和速度的测量。粒子滤波是一种近似最优的非线性滤波方法,其借助蒙特卡洛模拟可实现对待求参数概率密度函数的近似最优估计。将粒子滤波应用于协同无源探测解算,可实现非参数化的递推贝叶斯滤波,大幅提升无源探测的位置、速度测量精度。此外,还提出一种分块粒子滤波解算算法,通过降低粒子状态矢量维度,提升粒子空间覆盖性,在粒子数量受限的情况下,可进一步提升探测精度。Passive location system of multiple-node can locate and track the motive radar.Multiple spatially separated nodes passively detect radar signals at the same time to obtain the time difference of arrival(TDOA)and frequency difference of arrival(FDOA)of the signals reaching different nodes.The measurement of radar target position and speed information is completed through TDOA/FDOA joint calculation.Particle filter is an approximately optimal nonlinear filtering method that can achieve approximately optimal estimation of the probability density function of the parameter to be solved using Monte Carlo simulation.Nonparametric recursive Bayesian filtering can be achieved by applying particle filter to collaborative passive detection solution.The position and velocity measurement accuracy of passive detection is greatly improved.In addition,a block particle filter algorithm is proposed.By reducing the particle state vector dimension and improving particle space coverage,the detection accuracy can be further improved when the number of particles is limited.

关 键 词：多节点协同无源探测 TDOA/FDOA联合解算 粒子滤波 分块粒子滤波 

分 类 号：TN971[电子电信—信号与信息处理]