New Fusion Estimation Algorithm for Systematic Errors of Multiple Dissimilar Sensors
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摘要: 为解决由测向测时差无源被动传感器与主动传感器组网探测时异类多传感器系统误差估计问题,提出 了一种新的异类多传感器系统误差融合估计算法.首先,通过对主被动传感器进行组合并构建异类传感器系统 误差量测模型,实现了各组合传感器系统误差的实时估计;其次,通过建立多传感器融合估计结构,对多传感器 系统误差的组合估计信息进行融合并反馈,获得了各传感器系统误差的全局融合估计.蒙特卡罗仿真结果表明: 该算法能够对组网探测系统中各主、被动传感器的测向测时差及测距系统误差进行有效的融合估计,具有较高 的工程应用价值.Abstract: In order to solve the problem of systematic error estimation in a multiple dissimilar sensor network composed of passive sensors with DOA (direction of arrival) and TOA (time of arrival) measurements and active sensors, a new fusion estimation algorithm for systematic errors was proposed. With this algorithm, real-time estimation of the systematic errors of each sensor combination can be achieved through combining the active and passive sensors in pairs and establishing the systematic error model of dissimilar sensors. Then, the entire fusion estimation of the systematic errors of dissimilar sensors may be obtained through founding a multiple sensor fusion estimation structure and doing fusion and feedback of systematic error estimation for each sensor combination. The Monte-Carlo simulation result shows that the proposed algorithm can estimate the systematic errors effectively and is of engineering application value.
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