Research On High-resolution Imaging And Motion Compensation For Slow-speed Unmanned Aerial Vehicle SAR

The slow-speed unmanned aerial vehicle(UAV)SAR which is mounted on a small UAV platform equipped with a micro-SAR payload has advantages such as low power consumption,convenient takeoff and landing,and good concealment.It can realize flexible and low-cost detection in the battlefield environment and has become one of the research hotspots of SAR.However,high-resolution imaging and motion compensation of the slow-speed UAV SAR confront following problems: 1)the slow-speed UAV SAR can adopt the stepped-frequency technique to obtain a high range resolution.The non-ideal factors of the system lead to periodic range grating lobes in slow-speed UAV SAR,which affects the image quality and the target discrimination.Moreover,the existing range grating lobe suppression methods cannot realize the robust suppression of the range graing lobes in stepped-frequency SAR.2)Due to the airflow disturbance,the flight trajectory of UAV is very complex and the time-bandwidth product is small,the traditional motion compensation algorithms cannot realize the high-precision motion error estimation for slow-speed UAV SAR.3)Slow-speed UAV SAR can adopt a wide azimuth beam to obtain a high azimuth resolution.Influenced by the complex flight trajectory of UAV,a two-dimensional space-variant motion error is included in echo data and the existing wide-beam motion compensation algorithms cannot realize the ultra-high resolution imaging for slow-speed UAV SAR.This thesis has conducted in-depth research on the above issues of high-resolution imaging and motion compensation for slow-speed UAV SAR.The main research work and innovations are reflected by the following aspects:(1)The robust range grating lobe suppression algorithm for stepped-frequency SAR based on echo data is studied.Aiming at the problem that existing range grating lobe suppression methods cannot realize the robust suppression of range grating lobes in stepped-frequency SAR,the stepped-frequency SAR echo model is established,the formation mechanism of range grating lobes is analyzed,the quantitative relationship between the amplitude error and the phase error in the sub-band signal and range grating lobes in the wide-band synthesized signal is derived.Based on the derived quantitative relationship,three kinds of range grating lobe suppression algorithm based on echo data are proposed.After an algorithm performance comparison,the optimal range grating lobe suppression algorithm is determined,and the robust suppression of range grating lobes in stepped-frequency SAR is realized.The algorithm has been validated by real data,and provides a strong support for acquiring high-quality stepped-frequency SAR images.(2)The azimuth narrow-beam imaging and motion compensation algorithm for slow-speed UAV SAR based on echo data is studied.Aiming at the problem that traditional motion compensation algorithms cannot realize a high-precision motion error estimation for slow-speed UAV SAR,the echo model of slow-speed UAV SAR is established,the problems including the small time-bandwidth product of the azimuth signal,the ghost target in the imaging result,the range variance of the phase error and envelope error are analyzed.And then,a phase error estimation algorithm based on joint time-frequency iteration is proposed to solve the azimuth narrow-beam phase error estimation problem for slow-speed UAV SAR,and an estimation and compensation algorithm for the range-variant envelope error is proposed based on the image entropy to solve the estimation and compensation problem of range-variant envelope error in slow-speed UAV SAR.Besides,combined with the range grating lobe suppression algorithm for stepped-frequency SAR,an azimuth narrow-beam data processing flow for stepped-frequency slow-speed UAV SAR is given,which has been validated by real data and provides an effective method for acquiring high-resolution images of stepped-frequency slow-speed UAV SAR.(3)The azimuth wide-beam imaging and motion compensation algorithm for slow-speed UAV SAR based on echo data is studied.Aiming at the problem that existing wide-beam motion compensation algorithms cannot realize the ultra-high resolution imaging for slow-speed UAV SAR,the problem of the two-dimensional space-variant motion error in wide-beam data processing,the time-varing characteristic of the doppler frequency center,and the complex flight trajectory of the UAV platform are analyzed based on the existing slow-speed UAV SAR echo model.And then,a robust trajectory deviation estimation algorithm based on a combination of phase error estimation and trajectory deviation estimation is proposed,which solves the ultra-high resolution imaging problem for slow-speed UAV SAR.Besides,combined with the range grating lobe suppression algorithm for stepped-frequency SAR,an azimuth wide-beam data processing flow for stepped-frequency slow-speed UAV SAR is given,which has been validated by real data and provides an effective method for acquiring ultra-high resolution images of stepped-frequency slow-speed UAV SAR.