Data Association Based Fast Fault Detection for Low-Cost Micro/Nano -Satellite

Abstract

Under most circumstances, it is very important to achieve fast and real-time low-cost micro/nano-satellite fault detection. Regarding of faults as dynamic modes which observe through the multi-sensors, with probabilistic data association based on multi-sensor, we obtain the fault detection results according to the association probability and the threshold values. Joint Probabilistic Data Association (JPDA) algorithm is one of the effective ways for multi-sensor and multi-target tracking. We improve the JPDA algorithm as follows: At first, we propose an approximation method for constructing the confirmation matrix by removing the small probability events using the right threshold, and then, we present the mathematical division of the confirmation matrix according to the intersection area of the association gate of fault targets to be tracked; Finally, we compute the association probability of fault targets through attenuating the value of the public measurement. The simulation results show preliminarily that our improved JPDA algorithm saves the computational time greatly, and meet the requirements of fast and real-time fault detection effectively.