一种稳健的分布式检测算法

在多雷达分布式检测系统中各个雷达的信噪比各不相同且没有办法对实际的信噪比进行有效估计时，基于N选k融合的分布式检测策略最稳健的方法就是选择N选1融合，但是这种方法相对于系统所能达到的检测性能有很大的损失，该文提出了一种基于4元局部判决的方法，融合中心作3种N选k融合，然后将3种融合结果进行或运算以得到最终判决结果。仿真表明该方法比N选1融合具有更好的检测性能，能适应各个雷达输入信噪比剧烈变化的情况，是一种稳健的多传感器分布式检测方法。

A type of Robust Distributed Detection Algorithm

It is possible that the input signal-to-noise ratio of different radars may be different and their reliable estimation may be impossible in practical multiradar distributed detection scenario. So the most robust fusion rule is 1 out of N, which has severe signal-to-noise ratio loss comparable with the whole detection scheme’s potential. A new type of quarternary local decision based distributed detection algorithm is presented where the fusion center firstly perform three kinds of k out of N fusion and then fuses the obtained decision. Monte Carlo simulation revealed that the proposed algorithm has better detection performance than 1 out of N based scheme and can work well when the input SNRs change violently. So it is a robust distributed detection algorithm.