Distributed MIMO Active Target Tracking With Bernoulli Filter

In shallow ocean environments,the performance of passive sonar is limited in detection of quiet submarines and the small autonomous underwater vehicles.Meanwhile,active sonar faces the challenges of strong reverberation and a lot of interferences.With development of multiple input multiple output(MIMO)technology,the distributed MIMO processing takes advantage of spatial diversity for improvement of target detection which.has demonstrated a potential application prospect This thesis focuses on the distributed MIMO sonar processing which is combined with the Bernoulli filtering technology for improvement of detection of moving targets.In this thesis,a distributed MIMO sonar detection processing framework is built,during which the Doppler factor and the target position parameters are integrated into the signal model.The max-imum likelihood estimation is utilized to estimate the location of target.The constraint conditions are researched for the spatial configuration of the transmitters and receivers of MIMO sonar to exploit target diversity.For improvement of the receive signal-to-noise ratio,beamforming oper-ation is carried out at the reception end for enhancement of target echoes,and estimation of target bearings.Besides,the directional beams are utilized in the transmitting end to ensonify a target and suppress reverberation.Further,the pulse-cancellation method is utilized in post-processing to suppress reverberation and enhance target echoes.In the distributed MIMO sonar detection,measurements contain lots of reverberation and clut-ters besides targets.Meanwhile,it is not known when a target is present or absent Therefore,this paper studies the application of Bernoulli filtering in the detection of moving targets.Based on the analysis of Bayesian filtering and random finite set,the Bernoulli filtering iterative processing algorithm is deduced.In order to adapt to the need of multi-target tracking,the Bernoulli filtering algorithm is improved,that is,the posterior probability density function of single target is modified into the posterior probability density function of multi-target.In numerical simulations,we design two target tracking scenarios,single-target tracking and two-target tracking.Besides,two moving modes,cross movement,are considered in two-target tracking.The tracking results have validated the effectiveness of the improved Bernoulli filtering algorithm.In the lake trial of the distributed MIMO sonar detection of moving targets,the pulse cancellation method works well in suppressing reverberation and enhancing target echoes.The improved Bernoulli filtering algorithm can accurately estimates the trajectory of a moving target due to cancelling clutters.