Distributed MHE for Multi-Sensors Based on Measurements Compensation

In the actual multi-sensor network, the measurements of each sensor can be not enough to achieve the complete state estimation, due to its functional limitation or unexpected environmental factors. For this issue, this paper proposes a distributed moving horizon estimation (DMHE) algorithm based on the measurements compensation strategy. Considering the incomplete observability of each sensor’s measurements, a prediction of complete measurement is utilized by the sensor for compensation. To achieve the estimation consensus of all the sensors in the network, the moving horizon estimation approach is adopted for each sensor, based on its local measurements and its neighbor sensors’ transinformation. Then, a DMHE optimization problem is constructed and the associated implementation algorithm is presented. By implementing the presented DMHE algorithm, all the sensors in the network can give completed and precise state estimations without direct fusion of the state estimations, provided that the collection of all the sensors’ measurements is observable. The result is illustrated by a simulation.