Research On Location And Tracking Technology Of Multi-target Based On Passive Multi-sensor

With the rapid development of technology, active sensors are more easily to find enemy radar and echo signals are easily jammed, what lead to a sharp decline in detection performance. With the replacement of anti-radiation weapons, active sensors are in a very dangerous situation of future wars. With the development of all kinds of stealth technology, the performance of active sensors are even going down. Therefore,all countries have increasing emphasis on the study of passive sensors of contemporary national military.Multi-target passive location technology and multi-target tracking technology of multi-sensor are studied in this thesis.Firstly, single sensor’s direction finding cross location, the impact factors of direction finding cross location’s precision, and multi-target direction finding cross location are studied. Then simulated analysis is presented. Two passive location algorithms are introduced: the single objective weighted least squares method and the gradient descent method. It is difficult to remove the false targets of passive multi-target location. Three traditional methods are described and simulated: baseline least distance method, the data association and maximum likelihood method. For the distance differences of the right combination are all short and the distance differences of the wrong combination are sometimes long, the improved algorithm of baseline least distance method will be put forward. With the three traditional algorithms for performance comparison, simulated results show that there is still a highly accuracy associated rate with the improved algorithm in a high angle error situation.Secondly, single-target tracking technology is introduced. There are two kinds of situations: no clutter and clutter. In the case of no clutter a linear tracking algorithm(KF algorithm) and a non-linear tracking algorithm(EKF algorithm) are only described. In the case of clutter, single-target tracking algorithms have been described: NNSF algorithm and PDAF algorithm. The performance of the simulated analysis in the situations of different clutter density is presented.Finally, the multi-target tracking algorithm used commonly--JPDA algorithm is discussed. First, in the case of a single sensor, the function is achieved that the tracks are stable in multi-target tracking through its simulation of multi-target cross tracks. Second,with three structures: distributed multi-sensor, multi-stage multi-sensor(sequence and parallel) and centralized multi-sensor, JPDA is applied to the multi- sensor simulated analysis.