Research On Robust Bearing Estimation Method In Shallow Water

Sonar systems have been widely used as important equipments for underwater targetdetection, localization and tracking. In the complex ocean environment, the accurate androbust high-resolution estimation on direction of arrival is a key technology for newgeneration of sonar system.The mismatch of environment and sonar system parametersdegrades the performance of high-resolution beamforming in shallow water. In this thesis, theunderwater acoustic propagation model and the robust adaptive beamforming technology arecombined to overcome the influence of parameter mismatch on the DOA estimationperformance.Firstly, the mathematical tool, joint diagonalization, is used to deal with the spatial-timecorrelation matrix groups and the cumulant matrix groups to construct their jointdiagonalization structures. Through the uniform Jacobi rotation orthogonal jointdiagonalization, the corresponding eigenvalues are obtained and the spatial spectrum isredefined. After that, the performance of high-resolution DOA estimation algorithms can beimproved in the noise environment.Secondly, the influences of the optimization criterions and different mismatch factors areconsidered, the vector optimization robust adaptive beamforming algorithm is proposed toimprove the performance on DOA estimation. It can be proved that the existing robustadaptive beamforming algorithms can be unified into this vector optimization framework.Thispaper presents the process to solve the vector optimization problem by the second order coneprogram (SOCP) and an approximate analytic formula for the optimization weight vectorcalculation is obtained according to the Lagrange fast algorithm.Furthermore, this paperanalyzed the relationships between various factors for the optimal diagonal loading factor, andproved that the proposed algorithm is a generalized diagonal loading method. The numericalsimulation and experimental researches show that the proposed algorithm has a wideparameter selection range, and its output signal interference noise ratio (SINR) is not lowerthan other algorithms under the same bearing estimation bias. At the same time, the proposedalgorithm has higher peak to maximum sidelobe ratio (PSR) and narrower-3dB beamwidth,under the same signal noise ratio (SNR), snapshots, or steering vector errors. So it cansignificantly improve the DOA estimation resolution and the suppression ability for the noiseand interference.Thirdly, we established the array signal model according to the theory of image and analyzed the multipath effect on the bearing estimation for the situation of high-frequencyshort-range sonar system application. Then, combine the advantages of the vectoroptimization robust adaptive beamforming, such as a good tolerance to the constraintparameter selection, higher stability, and so on, we propose a vector optimization robustbearing estimation method in shallow water based on ray theory. Taking fully account of themultipath channel characteristics, we further consider the model mismatch influence, andimpose constraint conditions on the actual source vectors to improve the robustness for thehigh-resolution bearing estimation methods under the mismatch conditions. The simulationand experimental results show that the proposed method has higher peaks and lower sidelobelevel under the same conditions of the sediment parameter uncertainties, water depthuncertainties, the steering vector errors and other factors. So it has better DOA estimationresolution and noise interference suppression ability.Finally, for the situation of the shallow-water remote detecting sonar system application,we established the array signal model according to the normal mode theory and applied avector optimization method to impose constraint conditions on the actual source vectors inorder to improve the robustness for the high-resolution bearing estimation with theuncertainty of water thermocline depth、water depth, sound velocity gradient and other factorsin shallow water.In this paper, we discussed and analyzed the spatial spectrum structure, PSR,-3dB beamwidth, success probability, bearing estimation bias, and so on in detail. Thesimulation results show that the proposed algorithm has higher spectral peaks and lowersidelobe level under the conditions of different SNRs, incidence angles, water thermoclinedepth、water depth and sound velocity gradient uncertainties. At the same time, it keeps bettersuccess probability and bearing estimation accuracy.In this paper, the underwater channel model and the excellent robust adaptivebeamforming technique are combined to propose the highly robust bearing estimation methodin shallow water. It has been shown that the algorithm performance can be improvedsignificantly when the model parameters are mismatched.