Course information collection system

Abstract

The invention discloses a course information collection system. A CMOS (Complementary Metal Oxide Semiconductor) image sensor is adopted; a common six-degree-of-freedom mirco-electro-mechanical system gyroscope is combined; technologies such as image identification, plane transformation, pattern matching and fusion operation are adopted; course parameters of an unmanned aerial vehicle are calculated in real time; aiming at a small unmanned aerial vehicle flying at a low altitude and indoors, an autonomous course control solution with high navigation accuracy, high integration level and low cost is realized; the defects that signals can be shielded by objects during satellite navigation and signals can be easily affected by electromagnetic interference, signal drift and the like during inertial navigation can be overcome.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to a heading information collection system. Background technique [0002] The existing heading detection and control of UAVs mainly include the following methods: [0003] (1) Satellite positioning and navigation, using a satellite receiver to receive more than 6 satellite signals, can calculate the flight parameters such as the three-dimensional coordinate position and heading of the drone. This method is highly dependent on communication satellites. When drones fly at low altitudes such as high mountains and dense buildings, or indoors, the signal will be blocked or interrupted; and the satellite measurement data open to civilian use has large errors. [0004] (2) Inertial navigation, using high-precision MEMS micro-electromechanical gyroscopes to collect three-axis angular rate, three-axis acceleration and three-axis earth magnetic force signals, a t...

AI Technical Summary

Problems solved by technology

This method needs to use the acquisition sensor of the earth's magnetic force, the magnetic signal is weak, susceptible to electromagnetic information interference or object shielding, resulting in low accuracy and reliability of the calculated heading information; and calculation errors will accumulate over time, causing a drop in precision

[0005] (3) Celestial navigation, which determines the position and course of the UAV according to celestial bodies, but the cost is expensive, and the detection and calculation system is very complicated, so it is difficult to apply to the small UAV system

[0006] (4) Doppler navigation, using the Doppler effect for autonomous position and heading calculation, can calculate high-precision position, velocity and drift angle and other parameters, but the positioning error will increase with time, and when If the attitude of the aircraft exceeds the limit, the Doppler radar cannot work because it cannot receive the echo, and the navigation will fail

[0007] (5) Visual navigation, according to the gray value of each pixel in the image, dig out the heading parameter value, this technology involves image recognition and pattern matching technology, requires high sensor precision, fast image processing speed; and the cost is very high , there is no mature and popularized application

However, the geomagnetic information is relatively weak, and it is easily interfered by electromagnetic information or shielded by large objects, resulting in low accuracy of the detected heading information parameters, and will cause cumulative errors over time, so the reliability of the signal is also restricted

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