多站无源雷达多起伏目标检测前跟踪算法

摘要

针对多站无源雷达背景下多起伏目标同时检测和跟踪的问题，该文提出一种基于多目标多伯努利(MeMBer)滤波器的多起伏目标检测前跟踪(TBD)算法。由于起伏目标的平均信噪比(SNR)未知使得目标的回波幅度似然函数不确定，该文假定包络检波器的输出平均SNR服从先验的均匀分布，并对可能取值区间进行边缘化处理，得到一个估计的似然函数，基于该估计的似然函数，融合中心利用所有收发对的幅度观测信息对MeMBer滤波器的各个预测分量进行更新。仿真结果表明，该算法能够有效地同时检测和跟踪多起伏目标，并且在平均SNR大于9 dB时，其性能与平均SNR已知情况下的性能近似。%A Track-Before-Detect (TBD) algorithm is presented to jointly detect and track multiple fluctuating targets under passive multistatic radar system based on Multi-target Multi-Bernoulli (MeMBer) filter. Because the amplitude likelihood is uncertain due to the unknown mean Signal-to-Noise Ratio (SNR) of fluctuating targets, firstly a uniform prior distribution is assumed for the mean SNR corresponding to the envelope output, and a likelihood function is marginalized over the range of possible values. Based on this approximated likelihood function, the fusion centre uses all the amplitude measurements from each receiver transmitter pair to update the predicted Bernoulli components. Simulations show that the proposed algorithm can jointly detect and track multiple fluctuating targets effectively, furthermore, the performance is similar to the situation of the known mean SNR when the value of the mean SNR is higher than 9 dB.