Autonomous integrated navigation system

Abstract

The invention relates to an autonomous integrated navigation system which belongs to the technical field of navigation systems. The SINS (Strapdown Inertial Navigation System) / SAR (Synthetic Aperture Radar) / CNS (Celestial Navigation System) integrated navigation system takes SINS as a main navigation system and SAR and CNS as aided navigation systems and is established by the following steps: firstly, designing SINS / SAR and SINS / CNS navigation sub-filters, calculating to obtain two groups of local optimal estimation values and local optimal error covariance matrixes of the integrated navigation system state, then transmitting the two groups of local optimal estimation values into a main filter by a federal filter technology for fusion to obtain an overall optimal estimation value and an overall optimal error covariance matrix, and finally, performing real-time correction on the error according to the overall optimal estimation value so as to obtain an optimal estimation fusion algorithm of the SINS / SAR / CNS integrated navigation system. The autonomous integrated navigation system, disclosed by the invention, is less in calculation amount and high in reliability, is applicable to aircrafts in near space, aircrafts flying back and forth in the aerospace, aircrafts for carrying ballistic missiles, orbit spacecrafts and the like, and has wide application prospect.

Description

Technical field [0001] The invention relates to an autonomous integrated navigation system, belonging to the technical field of navigation systems. Background technique [0002] Autonomous navigation refers to the ability to accurately determine the position and speed of an aircraft without relying on ground personnel to measure and control. That is to say, when the aircraft is in an unknown, complex, and dynamic non-structural environment, without human intervention, through environmental perception, it can reach the desired destination while minimizing time or energy consumption. Autonomous navigation sensors have four characteristics: autonomous, real-time, passive and independent of ground information. [0003] Autonomous navigation is a new and highly challenging research topic for the development of my country's military aircraft (military satellites, military aircraft, cruise bombs, etc.). It is an inevitable trend for military aircraft navigation technology to develop tow...

AI Technical Summary

Problems solved by technology

Although they have achieved certain theoretical results in the application of integrated navigation systems, the following issues deserve attention: (1) The selection of importance functions directly affects the performance of PF, and it is very meaningful to carry out research on general criteria for the selection of PF importance functions ; Aiming at many practical problems, there have been many improved algorithms for selecting importance functions, but there are few methods for selecting importance functions in integrated navigation systems, which need further theoretical analysis; (2) Although the classic resampling method can be effective To overcome the lack of particles, but the amount of calculation increases with the increase of the number of particles, and the real-time performance of the system becomes poor. How to solve the realizability of particle filter in the integrated navigation system has become the main problem; (3) there is no mathematical theory at present. Answer the question under what conditions PF can converge, so it becomes very difficult to evaluate and analyze the performance of PF in the application of integrated navigation system

[0009] For UT transformation and UKF, although the accuracy proof of UT transformation can be obtained at present, the UKF algorithm cannot provide stability analysis like EKF, which affects its application in integrated navigation systems

There are many sampling strategies for UKF, which either have low precision, cannot accurately obtain high-order item information of nonlinear systems, and have poor filtering effects on non-Gaussian systems.

Either the accuracy is high, but the calculation is too complicated and the real-time performance is poor, which makes it difficult to realize the UKF algorithm in the integrated navigation system

[0010] It can be seen that the existing filtering technology cannot fully meet the requirements of high-precision autonomous navigation, and it is necessary to conduct in-depth research on the high-precision nonlinear algorithm and real-time data processing technology of autonomous navigation, in order to solve the basic theory and basic technology of military aircraft autonomous navigation Difficult problem seeks new ways to further improve combat capabilities of military aircraft

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