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中文摘要：
针对低检测概率下的无源定位问题，提出一种基于滑窗批处理的多传感器融合跟踪算法。通过将多个低检测概率的无源传感器组网，实现目标信息的空间积累，有效提高目标的检测概率。利用伪线性估计技术将非线性测量转换为伪线性测量，再对多传感器的伪线性测量进行基于滑窗批处理的最小二乘估计，得到目标局部最优解。仿真验证了算法的有效性和分析了参数的影响。结果表明，该算法能大幅提高无源定位系统对目标的检测概率，且能满足系统对跟踪精度及实时性的要求。
英文摘要：
For the problem of passive location under low detection probability, a multi-sensor fusion tracking algorithm based on sliding window batch technique is presented. Multiple low detection probability passive sensors are networked to spatially accumulate the target information and improve the detection probability. The nonlinear measurement is transformed to pseudo linear measurement by using pseudo linear estimation, and then the local optimal estimation of target state is achieved by a least squares sliding window batch algorithm. Simulations verify the validity of algorithm and analyze the effect of parameter. Results show that, the proposed method greatly improves the detection probability of the sensor network with acceptable tracking precision and real time requirement.
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