Real-time distributed sensor fusion for time-critical sensor readings

Abstract

The problem of dynamic distributed sensor fusion, where time critical sensor readings are fused concurrently by physically isolated modules, is considered. A large number of critical applications including target tracking, remote sensing, and autonomous vehicle navigation can depend on interpreting sensor readings in real time. Independent sensor modules receive partially contradictory data, but their answers must agree within computed accuracy bounds. Real-time constraints cause additional uncertainty factors. The dynamic nature of this problem requires that the problem be viewed in four dimensions and processed efficiently. We present a new method that robustly tolerates a limited number of component failures. This method has complexity O(f 4N log N), where N is the total number of modules and f is the number of faulty modules tolerated. Experimental results are given showing the merits of the proposed method.