基于短基线传感器网络的远场声源TDoA定位组合算法

Combination TDoA Localization Algorithms for Far-Field Sound Source Based on Short Base-Line Sensor Network

针对远场声源定位问题,提出到达时间差(TDoA)定位的短基线传感器网络方案.通常有一类定位算法无需估计初始点,而另一类算法则依赖初始估计值,提出将这2类方法相结合,设计出几种组合定位算法.主要思想是扬长避短,由第1类定位算法实现粗定位和输出初始估计位置,将其作为初始点输入给定位精度高和依赖初始值的第2类算法.提出利用蒙特卡洛法和简化的几何配置案例,计算定位算法的概率误差圆,论证了这种性能评估准则的可行性.通过对组合算法的概率误差圆进行数值分析,得出球形插值法与最小二乘方程差法的有机组合具有最优性能的结论,并分析了这种组合算法的盒图特性.根据不同的距离和声程差标准偏差进行模拟,以及采用野外真实场景下获得的声源数据进行试验,验证了结论.

For the localization problem of far-field sound source, the TDoA positioning scheme is proposed by using short base-line sensor network in the paper. Usually there is a kind of localization algorithms which do not need an estimated initial point; on the other hand, there is another kind of algorithms which depend on an initial estimation. In the paper the two kinds of methods are combined, and several combinational localization algorithms are developed. The main idea is that the first kind of localization algorithms are applied to finish a coarse positioning process and output an initial estimation location, which is inputted as the initial value of the second kind of algorithms with high positioning precision to take an advantage and supply a gap from them. The circular error probability of combinational localization algorithms is proposed to demonstrate the feasibility of the performance evaluation criterion, which is based on Monte-Carlo method and a simple case of geometry deployment. The circular error probability of combinational algorithms is numerically analyzed, and it is concluded that the combination of spherical interpolation and least squared equation error has an optimal performance. The box-plot character is experimented about this combination algorithm. According to the simulation experiments of different distances and standard deviation of sound range difference, and some sound source data obtained from the actual field scene, the conclusion of the paper has been verified.