Study of Long Baseline Navigation Optimization Solution Based on Redundancy measurement

Abstract

Generally speaking, the navigation of underwater targets is solved by the principle of spherical intersection. The number of array elements required for this method is fixed, but in the case of redundant array elements, they can’t be fully utilized. This paper presents two optimization methods based on redundancy measurement. One approach is the Gauss-Newton method and the other is Non linear Optimization method. The former, a non-linear least-squares optimization method that constantly revise regression coefficients through multiple iterations to minimize the sum of squared residuals, and the later, getting least squares solution of non linear redundant equations based on penalty constants. Simulation show that both methods are greatly affected by the initial position, the closer the distance between initial position to the target is, the smaller navigation error is. Under the same simulation conditions, the navigation accuracy of these two methods is higher than that of the ordinary spherical intersection method. The experiment proves these two methods can satisfy the navigation accuracy of the experiment in actual project.