Partial-Information-Based Distributed Filtering in Two-Targets Tracking Sensor Networks

In this paper, the partial-information-based (PIB) distributed filtering problem is addressed for two-targets tracking sensor networks. Different from existing distributed filters, the information communication between the sensors are assumed to have an imperfect physical condition-only partial information can be transmitted. Furthermore, for different pairs of adjacent nodes, the partly transmitted information can be completely distinct. The constraint on “partial information transmission” makes the filtering problem in sensor networks more challenging and practical. Some criteria concerning the connection gains are derived and used to design efficient PIB distributed filter to achieve the following objectives: i) the sensor network can efficiently tract two desired targets in the absence of disturbance and noise; ii) the filter satisfies certain given performance constraint. By using the regrouping method, which is an effective way to derive the main results, some simple yet effective criteria are derived for PIB distributed filtering. A numerical example is utilized to illustrate the effectiveness of the theoretical results.