An efficient multi-Bernoulli filter for tracking multiple maritime dim targets

Abstract

For the problem of tracking maritime dim targets, the sequential Monte–Carlo multi-Bernoulli track-before-detect (SMC-MB-TBD) method is popular. However, this method may face low tracking accuracy and tracking loss due to particle impoverishment and velocity uncertainty. In this study, a novel filter called position scaling and velocity correction multi-Bernoulli (PSVC-MB) is proposed to deal with this problem. First, particle position scaling is used to replace resampling in the SMC-MB-TBD method to deal with the lack of particle diversity. Second, when the target is stably tracked, the target velocity is extracted from the multi-frame information and used for re-estimation. Pseudo point measurements are calculated from the weighted average of all locations near the particle position, and the particle velocity will be continuously corrected with the pseudo point measurements. Simulation results verify the effectiveness of the proposed method at different low signal-to-clutter ratios (SCRs).

摘要

序贯蒙特卡罗多伯努利检测前跟踪(SMC-MB-TBD)方法广泛应用于海上弱目标的跟踪问题。由于粒子贫化和速度不确定性, 该方法存在跟踪精度低和跟踪损失的问题。为解决这一问题, 本文提出一种新的位置缩放和速度校正多伯努利滤波器(PSVC-MB)。首先, 采用粒子位置缩放代替SMC-MB-TBD方法中的重采样, 解决了粒子多样性不足的问题。其次, 当目标稳定跟踪时, 从多帧信息中提取目标速度并将其用于重新估计。由粒子位置附近所有位置的加权平均计算得到伪点测量值, 并通过伪点测量值对粒子速度进行连续修正。仿真结果验证了该方法在不同低信杂比条件下的有效性。