一种基于概率密度的多基阵声测被动定位算法

研究了基于概率密度分析的多基阵声测被动定位方法，并对定位算法和误差进行了理论分析和数值仿真。该方法将单基阵估计的目标方位看成是满足一定概率分布的一种可能的目标位置测量子集，根据每个单基阵得到的目标位置概率，计算目标位置在整个空间的概率密度分布，将概率密度最大点作为目标位置。研究结果表明，该声测被动定位方法的定位精度明显优于几何交叉定位法，具有重要的实用价值，它不仅可直接用于空中运动目标的探测和定位，而且也适用于地面运动目标的探测与定位。

A New Algorithm for Acoustic Passive Location with Multiple Arrays Based on the Distribution of Probability Density

The now generally used method for acoustic passive location of low altitude targets is, in our opinion, still not quite satisfactory. We propose a new method which, we believe, is better. Our method is a new method of acoustic passive location with multiple arrays, which is based on the distribution of probability density. In the full paper, we explain in much detail our new method, particularly its mathematical derivation; here we give only a briefing. In the new method, the result of the bearing estimation gained from one single array is considered as a probable measurements subset of the target location that is described by the probability density. Based on the probability density distributions of the target location obtained from all the arrays, the distribution of the general probability density of the target location in the whole space is calculated and the point of maximum probability density is regarded as the target placement. In our simulation research, we took a certain low altitude target. We used both the now generally used method and our new method. The location error of our new method is approximately 50% of that of the now generally used method.