Technology Research Of Multi-Sensor Synthesized Target Recognition Based On Sea Battlefield

The characteristic of modern war is that the battlefield extends from the land to the sea and the space. The situation that the various sensors gain is complicated and changes fast. Accurate enemy and selves' situation for the commander is not only basis of the battlefield situation and threat estimate, but also the basis for decision-making.The technology of target recognition has made a great achievement on recent decades. Overseas research of the target recognition is emphasized on target recognition system than arithmetic. In China the work of target recognition in some institutions about the algorithm has been researched before. In recent years, with some military equipment to the requirements of the target identification, some research institutes and institutions make active cooperation. The research of target recognition system and practical target recognition equipment is based on the practical system design.The research background in this paper is multi-sensor and single platform of the sea battlefield. The sensors of IFF, electronic surveillance, radar, sonar, photoelectric, A1S, and other information, are exploited. And the practical recognition model is established. The new target recognition arithmetic based on single platform is researched to get the target attribute, type, kind.This article selects the theory based on the rough collection of data mining method and the D-S evidence theory to carry on the target recognition of multi-sensors. The target recognition of is processed by the feature of the sea battlefield's multi-sensors. In this way, a pertinent arithmetic model is formed. The multi-sensor target classification of single period is based on the minimum risk rules. And the target classification of multiple periods is based on D-S evidence theory. Thus, the recognition is more exactitude. The synthesized identification frame based on single platform and multi-sensors put forward in this paper imitate the single platform and multi-sensors' target. The experiment demonstrates that multi-sensor's target recognition is more efficient and accurate than single-sensor. The feature of the technology based on rough sets can dig out hidden rules and get potential knowledge through the continuous accumulation of routines, refining and study.