基于极化分集技术的雷达抗干扰与优化检测研究

发布时间：2018-08-21 12:47

【摘要】：现代战争中的雷达面临着低空、超低空突防以及噪声、杂波背景下的目标检测等难题。随着雷达技术的不断进步,新体制极化雷达可以利用散射回波极化信息改善雷达系统的性能。以往的极化技术由于受到雷达极化状态的限制,一般只能利用水平和垂直极化(或左旋和右旋圆极化),没有充分挖掘极化信息处理的能力。新研制的极化雷达可以发射任意极化的脉冲。这种极化雷达与传统雷达相比,可以根据环境的先验知识来选取最优的发射极化,从而进一步增强雷达性能。因此本文针对现有的雷达抗干扰和检测中存在的问题,研究了基于极化分集技术的抗干扰及自适应优化检测算法。主要研究内容包括:针对低空、超低空突防产生的低空镜像角闪烁干扰,研究了对称极化分集对消算法抑制干扰;在均匀、部分均匀噪声环境以及非均匀杂波环境下研究了极化与波形自适应优化检测算法;文中引入了一种高效率的田口优化算法用于解决本文算法中的参数优化问题。首先,本文研究了低空、超低空突防产生的低空镜像角闪烁干扰的抑制问题。通过采用两点源闪烁模型,得出包含相位、幅度和极化参数的角闪烁线偏差公式;然后通过研究角闪烁线偏差函数和极化参数之间的关系,利用高效率的田口优化算法得到极值点,进而在极值点附近进行对称极化分集设计,保证每一集的角闪烁得到一定程度的抑制;最后极化分集对消之后的角闪烁线偏差得到了有效抑制。仿真实验结果表明,提出的对称极化分集对消抑制算法相比于其它方法,对低空镜像角闪烁干扰具有更佳的抑制效果。然后,本文研究了在均匀噪声环境中GLRT和AMF两个检测器的优化检测问题。通过研究两个检测器的检测性能随某一参数存在单调性,本文在检测性能保持不变的同时,将此含有极化信息的参数等价分解用于检测效率的提高,这种极化分解方法使得算法的乘法运算数目随着参数增多平方增加变为线性增加,从而可以大幅度提高检测效率;通过研究还发现这个参数与波形和极化信息密切相关,因此提出了两种波形设计方案,还提出了基于两个检测器自适应极化与波形设计联合优化检测算法,将优化检测问题转化为多参数的联合优化问题,进而应用田口优化算法解决优化问题。仿真实验结果表明,在均匀噪声环境中提出算法相比其它算法检测性能和效率获得了极大提高。再次,本文研究了在部分均匀噪声环境中ASD、Rao Test和Wald Test检测器的极化优化检测算法。研究了检测器检测概率的单调性;然后提出了一种极化优化检测算法用于提高检测器的检测性能;最后将上文提出的极化分解算法和自适应极化与波形设计联合优化检测算法同时用于ASD、Rao Test和Wald Test检测器的优化检测。仿真实验结果表明了提出算法在提高检测性能上的有效性。最后,本文研究了在非均匀杂波环境中的自适应极化与波形设计联合优化检测算法,首先引入一个包含非均匀杂波的信号检测模型,进而引用一个针对非均匀杂波非常稳定的对数GLRT检测器,这种检测器的判决能力只依赖于主要数据,而不依赖于次要数据、目标或者杂波的先验数据,很适合用于非均匀杂波环境中的目标检测。通过对一种极化优化检测算法的研究,将自适应极化与波形设计联合优化检测算法用于对数GLRT检测器来获得目标检测性能的提高。仿真实验结果表明,提出算法相比其它算法检测性能获得了极大改善。
[Abstract]:Radars in modern warfare are confronted with the problems of low altitude, ultra-low altitude penetration, noise and clutter detection. With the development of radar technology, polarization information of scattered echoes can be used to improve the performance of radar systems by new polarization radar systems. It can utilize horizontal and vertical polarization (or left-handed and right-handed circular polarization) without fully exploring the ability of polarization information processing. The newly developed polarization radar can emit pulses of arbitrary polarization. In this paper, the anti-jamming and adaptive optimization detection algorithm based on polarization diversity technology is studied for the existing problems in radar anti-jamming and detection. The main research contents include: For low-altitude, ultra-low-altitude penetration of low-altitude mirror angular glint interference, symmetrical polarization diversity cancellation algorithm is studied to suppress interference; Polarization and waveform adaptive optimization detection algorithm is studied in uniform, partially uniform noise environment and non-uniform clutter environment. An efficient Taguchi optimization algorithm is introduced to solve the parameter optimization problem in this algorithm. Firstly, the suppression of low-altitude mirror angular glint interference caused by low-altitude and ultra-low-altitude penetration is studied. The formula of angular scintillation line deviation including phase, amplitude and polarization parameters is obtained by using two-point source scintillation model; then the relationship between angular scintillation line deviation function and polarization parameters is studied, and the extremum points are obtained by Taguchi optimization algorithm with high efficiency, and then the symmetrical polarization diversity design is carried out near the extremum points to ensure each polarization parameter. The simulation results show that the proposed symmetrical polarization diversity cancellation algorithm is more effective than other methods in suppressing the low-altitude mirror angular glint interference. Then, we study the in-equalization algorithm. The problem of optimal detection of GLRT and AMF detectors in uniform noise environment is studied. By studying the monotonicity of detection performance of two detectors with a certain parameter, this paper applies the equivalent decomposition of parameters containing polarization information to improve detection efficiency while the detection performance remains unchanged. This polarization decomposition method makes multiplication of the algorithm. The number of operations increases linearly with the increase of the square of the parameters, which can greatly improve the detection efficiency. It is also found that this parameter is closely related to the waveform and polarization information. Therefore, two waveform design schemes are proposed, and a joint optimization detection algorithm based on two detectors adaptive polarization and waveform design is proposed. The optimization detection problem is transformed into a multi-parameter joint optimization problem, and then Taguchi optimization algorithm is applied to solve the optimization problem. Simulation results show that the detection performance and efficiency of the proposed algorithm in uniform noise environment are greatly improved compared with other algorithms. Thirdly, this paper studies ASD, Rao Test and Rao Test in partially uniform noise environment. The monotonicity of detector detection probability is studied. Then a polarization optimization detection algorithm is proposed to improve the detection performance of Wald Test detector. Finally, the polarization decomposition algorithm and the adaptive polarization and waveform design joint optimization detection algorithm are applied to ASD, Rao Test and Wa simultaneously. The simulation results show that the proposed algorithm is effective in improving the detection performance. Finally, the joint optimization detection algorithm of adaptive polarization and waveform design in inhomogeneous clutter environment is studied. Firstly, a signal detection model including inhomogeneous clutter is introduced, and then a needle is cited. Logarithmic GLRT detectors with very stable nonuniform clutter are suitable for target detection in nonuniform clutter environments because their decision ability depends only on primary data and does not depend on secondary data, target or clutter prior data. The proposed algorithm is applied to the logarithmic GLRT detector to improve the performance of target detection. Simulation results show that the performance of the proposed algorithm is greatly improved compared with other algorithms.
【学位授予单位】：哈尔滨工程大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN974

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