基于粒子滤波的被动多基站跟踪算法

针对被动多基站跟踪的实际应用，提出了基于粒子滤波的被动多基站跟踪方法。该方法首先利用两个基站的观测数据融合目标位置，并用第三个基站的观测数据对目标位置进行检验，消除了错误融合位置；然后，推导了被动多基站粒子滤波模型，并根据被动多基站跟踪的特点，提出了顺序重抽样方法，有效地解决了被动多基站跟踪中的高度非线性、非高斯的影响；最后，给出了算法的性能仿真比较。仿真结果表明提出的方法性能明显优于其他跟踪方法（如PMHT、IMM-PDA）。

A Novel Passive Tracking Algorithm Using Sensor-Array Based on Particle Filter

Aiming at the application of passive tracking based on sensor-array,a new passive tracking using sensor-array based on particle filter was proposed.Firstly,the "fake points" could be almost entirely and exactly deleted with the aids of the sensor-array at the expense of an additional sensor.Secondly,considered the fact that the measurements gotten from each array were independent in passive tracking system,a novel sequential particle filter using sensor-array with improved distribution was proposed.At last,in a simulation study we compared this approach algorithm with traditional tracking methods.The simulation results show that the proposed method can greatly improve the state estimation precision of sensor-array passive tracking system.