New Fusion Estimation Algorithm for Systematic Errors of Multiple Dissimilar Sensors

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.