High-frequency motion error compensation algorithm of small unmanned aerial vehicle BiSAR system

Abstract

According to the high-frequency motion error compensation algorithm of the small unmanned aerial vehicle-mounted BiSAR system, the azimuth error phases of N pieces of strong point information are obtained by performing coarse imaging on echo data of the small unmanned aerial vehicle-mounted BiSAR system, and N is a positive integer; fourier transform is carried out on the azimuth error phase of the strong point information to obtain time-frequency information of the strong point information, and low-frequency signal components of the time-frequency information of the strong point information are filtered out according to a time-frequency ridge of the time-frequency information of the strong point information to obtain high-frequency signal components of the time-frequency information; inverse radon transformation is performed on the high-frequency signal component to obtain error estimation values of the maximum frequency offset, the frequency and the initial phase of the high-frequency signal component; estimated values of the frequency and the initial phase are obtained by using a weighted average algorithm, and an estimated value of the maximum frequency offset is obtained by using a least square method; and the high-frequency signal component in the distance direction is compensated according to the estimated value of the high-frequency signal component. Space-variant motion compensation and low-frequency motion compensation of high-frequency errors of a BiSAR system are achieved, and good focusing of SAR images is achieved.

Description

technical field [0001] The invention belongs to the technical field of bistatic synthetic aperture radar, and in particular relates to a high-frequency motion error compensation algorithm of a small UAV-borne BiSAR (Stripmap BiSAR, bistatic synthetic aperture radar) system. Background technique [0002] The small UAV platform has the characteristics of light weight, small size, flexibility, and cheapness, and is used as a carrier platform by more and more SAR systems. During the working process of the SAR system, the small UAV platform is easily disturbed by the external environment because of its light weight, and its flight trajectory and flight attitude will change greatly during the movement. [0003] The carrier platforms of traditional SAR systems are mostly large transport planes or satellites. The platforms are large in size and weight, and have good stability. Therefore, the motion errors mainly come from the accuracy of the inertial navigation system, which is refl...

AI Technical Summary

Problems solved by technology

However, unlike traditional SAR system carriers, for small unmanned aerial vehicle systems, the platform will not only introduce low-frequency motion errors during the movement process, but also introduce high-frequency motion errors due to the jitter of the aircraft attitude

[0004]Because small drones have great limitations on load and power consumption, it is impossible to install a high-precision inertial navigation system, so these high-frequency movements cannot be recorded. High-frequency errors in the trajectory

In addition, the separation of the transceiver platform in the BiSAR system may introduce high-frequency motion errors, making the error impact more complicated

When the working frequency band of the system is high, such as the Ku band, the high-frequency jitter with millimeter-level amplitude will have a great impact on the imaging results

Most of the existing motion compensation algorithms only consider low-frequency errors in common situations. However, high-frequency error motion compensation algorithms based on high-precision inertial navigation information are difficult for light and small SAR platforms.

At the same time, the algorithm for compensating multi-component motion errors usually uses direct search to estimate the error parameters, but it requires a lot of time and computing resources, and it is difficult to realize real-time processing of inertial navigation data

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