Marine SINS Self-Alignment Method in Complex Interference Environment Based on MEEMD Algorithm

Abstract

It is difficult to rapidly and accurately achieve alignment under complicated interferential environmental conditions with a marine strapdown inertial navigation system (SINS) subject to angular swaying interference and linear motion interference. To solve this problem, an SINS self-alignment algorithm in a complex interference environment is presented in this article. For the angular motion disturbance problem, we used the attitude-updating algorithm in the coagulation inertial coordinate system to reflect the carrier’s attitude change in real time under the swaying interference so as to eliminate the influence of angular motion disturbance. To solve the problem of linear motion interference, we first use Fourier transform analysis (FFT) to analyze the frequency characteristics of linear motion interference signals. We then adaptively decompose the original signal into a series of signal components with different time scales and local characteristics according to the amplitude and frequency using the modified ensemble empirical mode decomposition (MEEMD) algorithm. Finally, we remove and reconstruct the disturbing signal components according to the frequency characteristics of the disturbing signal to filter the line motion disturbing signal. We use the MEEMD algorithm to conduct a ship alignment test. After pre-filtering by MEEMD, high accuracy can be achieved after 100 s of alignment, and the mean square error of the heading angle is 2.85′. The test results show that the MEEMD method has a good noise removal effect. The anti-jamming initial alignment algorithm based on the MEEMD algorithm has the ability to suppress the interference of angular motion and linear motion and achieve high-precision anti-jamming initial alignment under the complicated interferential environmental conditions with angular swaying interference and linear motion interference.