基于多传感器的雷达对抗侦察数据融合算法

为提升复杂电磁环境下雷达对抗侦察系统的可靠性及抗干扰能力, 提出了一种基于多传感器融合的综合权值估计算法。首先由各传感器对原始数据进行分批估计得到局部期望及方差, 然后利用四分位离散度剔除异常数据, 接着针对局部估计结果通过测度算子以及自适应融合估计算法分别确定各传感器权重, 最后利用综合权重进行加权得到融合结果。仿真结果表明, 所提算法在不同情况下均能得到较高的融合精度, 较现有算法具有更好的适应能力及准确性。

Data fusion algorithm for radar countermeasures and reconnaissance based on multi-sensor

To improve the reliability and anti-jamming capability of radar countermeasures and reconnaissance systems in complex electromagnetic environments, a comprehensive weight estimation algorithm based on multi-sensor fusion is proposed. Firstly, the original data is estimated by each sensor in batches to obtain the local expectations and variances. Secondly, the quartile dispersion is used to eliminate the abnormal data. Thirdly, the weight of each sensor is ascertained by the measurement operator and the adaptive fusion estimation algorithm for the local estimation results. Finally, the comprehensive weight is used for weighting to obtain the fusion result. Simulation results show that the proposed algorithm can obtain higher fusion accuracy under different conditions, and has better adaptability and accuracy than existing algorithms.