传感器测量衰减下的水下目标纯方位跟踪算法

为解决多传感器水下目标纯方位跟踪中的传感器测量衰减问题,建立水下目标静态多传感器纯方位跟踪模型,将传感器测量衰减建模为统计特性已知的随机变量,基于融合中心接收到的各水声传感器的原始测量值,设计了一种集中式状态估计器结构,利用最小方差方法推导出最优的集中式目标状态估计增益。通过算例仿真可以得出,所提出的算法能够在水声传感器不做机动的前提下跟踪目标,弥补了单个水声传感器观测性不足的缺点,对比传统的集中式Kalman估计器,具有更高的精度,能够有效解决传感器测量衰减问题。

Multi-Sensor Bearing-Only Underwater Target Trackingargorithm forSensor Measurement Attenuation

In order to solve the problem of sensor measurement attenuation in multi-sensors underwater target tracking by bearing-only method,a static bearing-only target tracking model based on underwater static multi-sensors is established.The sensor measurement attenuation is modeled as random variables with known statistical characteristics.Based on the original measurement values of each underwater acoustic sensor received by the fusion center,a centralized state estimator structure is designed.The optimal gain of centralized target state estimation is derived by variance method.Simulation results show that the proposed algorithm can track the target without maneuvering the underwater acoustic sensor,and make up for the shortcomings of single underwater acoustic sensor.Compared with the traditional centralized Kalman estimator,it has higher accuracy and can effectively solve the sensor measurement attenuation problem.