基于干涉合成孔径激光雷达的三维成像算法研究

发布时间：2018-07-10 09:51

本文选题：合成孔径激光雷达 + 干涉测量　；参考：《哈尔滨工业大学》2017年硕士论文

【摘要】：干涉合成孔径激光雷达(In SAL,Interferometric Synthetic Aperture Ladar)是一种通过合成孔径技术以及干涉法获得目标三维信息的激光雷达,在军事与国防领域方面都有着重大的研究价值。In SAL图像处理算法可以实现干涉图到目标高程信息的处理。当前In SAL系统大都为了获得高分辨率增加了波长调制修正误差的结构使得系统整体较为复杂,而且干涉合成孔径雷达(In SAR,Interferometric Synthetic Aperture Radar)算法在In SAL系统的直接移植存在精度低的问题。对系统进行优化有利于在特定的环境下减小系统的体积与重量,而对算法的优化有利于In SAL系统成像获得更高的精度;本文完成了In SAL系统的优化,可以解决当前In SAL系统体积、重量大的问题;改进了处理算法提高了成像精度,并通过实验进行了验证。本论文首先综述分析了合成孔径雷达三维成像领域的国内外动态。目前国内外在雷达系统方面,对于In SAL三维成像的实验室验证已经实现,而且相关研究主要集中在目标高程信息获取的多种方式的研究。在算法优化方面,对于In SAR的处理算法研究较为深入,研究范围涵盖了诸如相位误差、电离层影响、解缠效率低等方面。首先本论文针对在特定的应用背景下,对雷达的体积和重量提出的要求,而当前In SAL系统大都较为复杂的问题,设计了一种优化的In SAL系统结构,通过调制器加载线性调频信号,省去了因为调制波长所导致的误差修正步骤,并分析了该系统的分辨率与信噪比特性,结果表明可以在保证识别目标的分辨率与信噪比的条件下,实现系统重量与体积的减小。然后本文针对传统In SAR图像配准算法配准In SAL图像精度低的问题,分析了In SAL系统中散粒噪声和热噪声对传统配准算法的影响以及各种配准测度的特性,研究了平均波动函数法以及谱配准法的实现流程并进行仿真分析。进一步,分析了In SAR系统与In SAL系统在系统噪声方面的差别,提出了一种基于谱配准法与最大相关函数法的改进的谱配准算法,并进行了仿真实验,结果表明这种改进的谱配准算法的配准精度提高了1.43%。而在配准速度上也有所提高。之后本文针对散粒噪声与热噪声影响传统相位解缠算法精度的问题,分析了质量引导解缠法、最小范数法以及基于网络规划解缠法等理论,进行了仿真实验研究了三种算法处理In SAL干涉图的解缠效果,仿真结果表明与其他两种算法相比,质量引导相位解缠算法对In SAL干涉图的解缠效果更好,并发现这种算法解缠结果存在的不均匀误差的问题。针对这一问题,提出了基于区域滤波的质量引导相位解缠算法优化方法,给出了区域滤波的具体实现方式并进行了仿真实验,仿真结果表明区域滤波质量引导相位解缠法可以有效降低相位误差20.86%。最后搭建实验系统并进行验证性实验。分析可能影响实验的设备参数并选取合适的仪器与设备,结合优化后的In SAL系统搭建实验系统。通过实验证明了优化的In SAL系统的可行性,以及改进的谱配准算法和区域滤波质量引导相位解缠算法优化的有效性。
[Abstract]:Interferometric synthetic aperture laser radar (In SAL, Interferometric Synthetic Aperture Ladar) is a kind of laser radar that obtains three-dimensional information of target through synthetic aperture technology and interference method. It has great research value in military and national defense fields..In SAL image processing algorithm can realize interferogram to target elevation information. Processing. Most of the current In SAL systems have increased the structure of the wavelength modulation correction error to make the system more complex, and the interference synthetic aperture radar (In SAR, Interferometric Synthetic Aperture Radar) algorithm in the In SAL system directly transplanted in the low precision problem. In a specific environment, the volume and weight of the system are reduced, and the optimization of the algorithm is beneficial to the higher precision of the In SAL system imaging. The optimization of the In SAL system is completed in this paper, which can solve the problem of the volume and weight of the In SAL system at present, and improve the processing algorithm to improve the imaging precision. This paper has been verified by experiments. At first, the domestic and foreign developments in the 3D imaging field of synthetic aperture radar are reviewed and analyzed. At present, the laboratory verification of In SAL 3D imaging has been realized in the field of radar system both at home and abroad, and the related research is mainly focused on the research of various ways of obtaining the target elevation information. In the aspect of algorithm optimization, the processing algorithm for In SAR The research scope covers such aspects as phase error, ionosphere influence and low unwrapping efficiency. Firstly, this paper aims at the requirements of the volume and weight of radar in the specific application background, and the current In SAL system is mostly complex, and designs an optimized In SAL system structure, through the modulator. The linear frequency modulation signal is loaded, and the error correction step caused by the modulation wavelength is omitted. The resolution and signal to noise ratio characteristics of the system are analyzed. The results show that the system can reduce the weight and volume of the system under the condition of ensuring the resolution of the target and the signal to noise ratio. Then this paper is based on the traditional In SAR image registration algorithm. In the problem of low precision of quasi In SAL image, the influence of granular noise and thermal noise on the traditional registration algorithm in In SAL system and the characteristics of various registration measures are analyzed. The implementation process of the average wave function method and the spectrum registration method are studied and the simulation analysis is carried out. Further, the noise aspect of the In SAR system and the In SAL system is analyzed. In this paper, an improved spectral registration algorithm based on the spectral registration method and the maximum correlation function method is proposed, and the simulation experiments are carried out. The results show that the registration accuracy of the improved spectral registration algorithm is improved by 1.43%. and the registration speed is improved. The problem of the method precision is analyzed. The quality guided unwrapping method, the minimum norm method and the network programming unwrapping method are analyzed. The simulation experiments are carried out to study the unwrapping results of the three algorithms to deal with the In SAL interferogram. The simulation results show that the quality guided phase unwrapping algorithm is more effective for the In SAL interferogram than the other two algorithms. Well, the problem of inhomogeneous error in the unwrapping results of this algorithm is found. In view of this problem, an optimization method of quality guided phase unwrapping algorithm based on regional filtering is proposed, the concrete realization method of regional filtering is given and the simulation experiment is carried out. The simulation results show that the region filtering quality guided phase unwrapping method can be effective. In the end, the phase error 20.86%. is reduced and the experimental system is built. The equipment parameters which may affect the experiment are analyzed and the suitable instrument and equipment are selected. The experimental system is built with the optimized In SAL system. The feasibility of the optimized In SAL system and the improved spectral registration algorithm and the regional filtering quality are proved by the experiment. The effectiveness of the optimization of the quantity guided phase unwrapping algorithm.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN958.98

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