Inertial sensor aliasing interference signal separation method

Abstract

The invention discloses an inertial sensor aliasing interference signal separation method. The method comprises the following steps that (1) characteristic analysis is conducted on inertial sensor output aliasing signals, and the frequency characteristics of different interference source signals are determined; (2) a threshold function, a wavelet basis and a decomposition level are selected to conduct wavelet filtering on a low frequency section signal in the aliasing signals according to the characteristics of the low frequency section signal; (3) aiming at the high frequency aliasing interference signal subjected to wavelet filtering, N internal empirical mode functions (IMFs) are acquired through self-adapting decomposition of empirical mode decomposition (EEMD); (4) the information content of IMFs is eta, and the number p of the needed IMFs components is calculated and obtained when the eta is larger than or equal to 90 degrees; (5) A PCA algorithm is utilized for dropping N-dimensional IMFs to be P-dimensional; and (6) P-dimensional IMFs is taken as an observation signal, and an appropriate blind source separation algorithm is selected to separate interference source signals at different frequency sections in the high frequency aliasing interference signal. The inertial sensor aliasing interference signal separation method greatly reduces too much man-made experience selections in the signal separation process, and the adaptivity is relatively high.

Description

technical field [0001] The invention belongs to the field of digital signal processing, and in particular relates to a method for separating aliasing signals of inertial sensors, which is used to realize the separation of aliasing interference signals output by inertial sensors in a photoelectric tracking system of a motion platform. Background technique [0002] For the ATP system on a moving carrier, the visual axis will vibrate due to the movement of the carrier and external interference to the carrier, causing the system to deviate from the tracking target, resulting in a decrease in tracking performance. Therefore, the system usually uses an inertial stabilization platform to isolate the interference of the system to the carrier and ensure the stability of the system's boresight. In order to improve the disturbance suppression ability of the inertial stable platform, it is necessary to control all kinds of disturbances received by the system separately. One of the diffi...

AI Technical Summary

Problems solved by technology

Multiple Kalman filtering needs to establish an accurate mathematical model of the interference signal multiple times, and the interference of the inertial sensor is more complicated, it is difficult to obtain an accurate model of each interference source, and the inaccurate

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