Unmanned aerial vehicle SAR self-focusing method based on aerial carrier track deviation estimation

Abstract

The invention discloses an unmanned aerial vehicle SAR self-focusing method based on aerial carrier track deviation estimation. According to the method, the aerial carrier track deviation is estimatedon the basis of echo data, and the accurate estimation of the aerial carrier track deviation is realized by utilizing a coarse-to-fine step-by-step self-focusing strategy, so that the two-dimensionalspace-variant property of motion errors is fundamentally solved, the low-speed unmanned aerial vehicle-mounted SAR self-focusing is realized, and a high-resolution unmanned aerial vehicle-mounted SARimage is obtained.

Description

technical field [0001] The invention relates to the technical field of synthetic aperture radar, in particular to an unmanned aerial vehicle-borne synthetic aperture radar (SAR) self-focusing method based on aircraft track deviation estimation. Background technique [0002] UAV-borne SAR is a technology that uses UAVs for synthetic aperture imaging, which can achieve all-day and all-weather earth observation, and is widely used in terrain exploration and battlefield reconnaissance. At present, azimuth wide-beam imaging and motion compensation for slow UAV-borne SAR have become a hot spot in the development of UAV-borne SAR technology. [0003] Due to its small size (such as 20 cm square), light weight (such as a 1 kg UAV-borne SAR system), low flying altitude and slow flying speed (such as a flying height of 200 meters and a flying speed of 20 meters per second), it is affected by airflow. Influenced by its own simple dynamic structure, the flight trajectory of slow-speed U...

AI Technical Summary

Problems solved by technology

The first type is based on high-precision inertial navigation system (INS) for motion compensation or back projection (BP) imaging. However, when the radar works in the high-frequency band, the accuracy of INS often cannot meet the imaging accuracy requirements, resulting in defocused imaging results. Moreover, for small unmanned aerial vehicles, due to the strict constraints of load volume and load, it is often impossible to equip high-precision inertial navigation

The second type is the self-focusing method based on back-projection imaging. This type of method ignores the envelope error and estimates the local phase error based on the echo data, which cannot adapt to the space-varying envelope error.

The third category is to estimate and fit the second-order space-variant coefficient of the phase error based on the Phase Gradient Autofocus Algorithm (PGA), which has model approximation errors

[0005] In summary, there is currently no effective azimuth wide-beam imaging and motion compensation method for slow UAV-borne SAR

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