Multi-target passive positioning method based on underwater sensor network

Abstract

The invention belongs to the field of multi-sensor fusion estimation, and provides a multi-target passive positioning method based on an underwater sensor network. A strategy of combining feature level and decision level information fusion is adopted. Multi-target detection based on an underwater acoustic sensor network has the problems of high energy consumption, low positioning precision, largetime delay and the like. Aiming at the defects, the algorithm provided by the invention performs multi-target azimuth estimation on a single node array, extracts the characteristics of a plurality oftarget signals, transmits the characteristics to a fusion center for processing, performs azimuth estimation on multiple targets in real time, and further obtains position information. The algorithm reduces the communication information amount between nodes while improving the accuracy of multi-target position estimation. Therefore, the method has important practical significance for solving the actual underwater multi-target passive positioning problem.

Description

technical field [0001] The invention belongs to the field of multi-sensor fusion estimation, in particular to a multi-target passive positioning method based on an underwater sensor network. Background technique [0002] Underwater target detection is an essential part of ocean monitoring network and ocean early warning system. In the military, non-cooperative targets such as submarines have seriously threatened my country's maritime security. In order to continuously monitor the marine environment for a long time, the underwater sensor network will become an important technical support. In the civilian field, underwater sensor networks can also be used for search and rescue of underwater targets, intelligent transportation monitoring, marine biological detection, etc. However, the traditional active detection method will consume a lot of energy, which is not conducive to the maintenance of the underwater sensor network, and it is easy to expose one's own position. However...

AI Technical Summary

Problems solved by technology

However, due to the influence of various complex noises underwater, the current passive detection based on the single-vector hydrophone array has low precision and poor effect, and it is difficult to obtain accurate orientation information of multiple targets under low signal-to-noise ratio, while active detection will consume a huge amount of time. energy

The complexity of the underwater environment will lead to long underwater acoustic communication delays and high bit error rates, so it is difficult to directly integrate measurement information between different hydrophone arrays, and data synchronization cannot be performed

Images