雷达机动目标长时间积累信号处理算法研究
发布时间：2018-08-01 10:03
【摘要】：为提高现代雷达对微弱机动目标的探测能力，通常通过增加积累时间来提高检测前信噪比。但是由于目标的机动运动特性，长时间积累过程中目标易发生距离徙动和多普勒扩散，导致传统的积累方法效能降低。基于此，本文研究高速机动目标回波距离/多普勒徙动校正方法以及长积累时间下微弱机动目标的参数估计算法。 本文的主要研究内容如下： 1、针对单目标场景下的高速机动目标在长时间积累过程中出现的距离徙动和多普勒扩散问题，提出了MDP-KTRFT参数估计算法。该算法利用二阶Keystone变换校正目标回波包络的距离弯曲，然后利用改进的dechirping估计目标加速度并补偿目标方位向的二次相位，最后通过一阶RFT技术实现目标的能量聚集并获得高精度的目标运动参数和初始距离的估计结果。 2、针对多目标场景下的高速机动目标在长时间积累过程中出现的距离徙动和多普勒扩散问题，提出了FrFT-KTRFT参数估计算法。该算法首先利用二阶Keystone变换校正目标回波包络的距离弯曲，然后利用分数阶傅里叶变换（FrFT）估计目标加速度并补偿目标方位向的二次相位，最后通过一阶RFT技术实现目标能量的聚集并获得多个目标的高精度的运动参数和初始距离的估计结果。MDP-KTRFT算法和FrFT-KTRFT算法均能在目标运动信息未知的前提下有效补偿目标的距离徙动和时变多普勒频率，同时能够克服多普勒模糊的限制，获得高的参数估计精度。通过与二阶RFT算法进行比较可看出，两种算法在较低运算量的情况下仍能获得精确的目标参数估计结果。 3、针对现有参数估计算法需进行搜索处理的问题，提出了一种基于Keystone变换和Lv’s Transform（LVT）的多目标运动参数联合估计算法，该算法无需进行多次迭代搜索，同时能够解决传统LVT算法估计精度受距离徙动影响的问题，并进一步推导出了所提算法的信噪比门限。 4、考虑到高速运动目标的参数对应的频率和调频率有可能超出LVT估计器相应的主值区间，导致参数估计错误，为此提出了一种基于子带双频共轭和LVT相结合的改进的参数估计算法。该算法通过构造两个具有不同中心频率的子带信号，并对这两个信号平移后进行共轭相乘处理得到合成信号，最后对该合成信号进行Keystone变换和LVT处理。仿真和实测数据处理结果表明，该算法能够同时对多个目标的距离徙动进行校正，有效降低了参数搜索的运算复杂度。 5、针对低信噪比下无速度模糊的运动目标参数估计问题，提出了一种基于分段Keystone变换和频域LVT相结合的参数估计算法（SKT-FLVT）。该算法首先采用分段Keystone变换校正线性距离徙动，然后对各段回波数据在方位向进行快速傅立叶变换（FFT）处理，并在段间采用Keystone变换校正频率走动，最后采用LVT处理完成参数估计。该算法中的Keystone变换与LVT处理均易于并行计算，有效提升了计算效率的同时降低了存储量。仿真结果表明，该算法能够在运动目标参数信息未知的情况下直接进行精确的参数估计。 6、对于存在速度模糊的运动目标参数估计问题，提出了基于模糊数估计的SKT-FLVT算法。该算法首先采用分段Keystone变换校正线性距离徙动，然后对速度模糊数进行一维搜索来估计模糊数，之后对各段回波数据在方位向进行FFT处理，，并在段间采用Keystone变换校正频率走动，最后采用LVT处理完成参数估计。仿真和实测数据处理结果表明，所提算法仅需对速度模糊数进行一维搜索，即可在低信噪比下获得精确的运动目标参数估计结果。
[Abstract]:In order to improve the detection ability of modern radar for weak maneuvering target, it usually increases the signal to noise ratio before detection by increasing the accumulation time. However, due to the maneuvering characteristics of the target, the target is prone to distance migration and Doppler diffusion during the long time accumulation, which leads to the reduction of the traditional method of accumulation. Based on this, this paper studies the high speed machine. Moving target echo distance / Doppler migration correction method and parameter estimation algorithm for weak maneuvering target with long accumulation time.
The main contents of this paper are as follows:
1, the MDP-KTRFT parameter estimation algorithm is proposed for the distance migration and Doppler diffusion problem during the long time accumulation of the high speed maneuvering target in a single target scene. The algorithm uses the two order Keystone transform to correct the distance bending of the target echo envelope, and then uses the modified dechirping to estimate the target acceleration and compensate the target. The second phase of azimuth direction is used to realize the energy gathering of the target through the first-order RFT technique, and the high-precision estimation results of target motion parameters and initial distance are obtained.
2, the FrFT-KTRFT parameter estimation algorithm is proposed for the distance migration and Doppler diffusion problem during the long time accumulation of the high-speed maneuvering target in the multi-target scene. The algorithm first uses the two order Keystone transform to correct the distance bending of the target echo envelope, and then uses the fractional Fourier transform (FrFT) to estimate the target acceleration. The degree and compensation of the two phase of the direction of the target, and finally through the first order RFT technology to achieve the aggregation of the target energy and obtain the high precision motion parameters and the initial distance of multiple targets, the.MDP-KTRFT algorithm and the FrFT-KTRFT algorithm can effectively compensate the distance migration and time variation of the target under the premise of the unknown target motion information. The Doppler frequency can overcome the Doppler's fuzzy limit and obtain high parameter estimation precision. By comparing with the two order RFT algorithm, it can be seen that the two algorithms can still obtain accurate target parameter estimation results in the case of lower computation.
3, in view of the problem that the existing parameter estimation algorithms need to be searched and processed, a joint estimation algorithm based on Keystone transform and Lv 's Transform (LVT) is proposed. The algorithm does not need multiple iterative search, and can solve the problem of the traditional LVT estimation precision affected by the distance migration, and further deduce the problem. The threshold of the signal-to-noise ratio of the proposed algorithm is given.
4, considering that the frequency and frequency of the parameters corresponding to the high speed moving target may exceed the corresponding main value interval of the LVT estimator, the parameter estimation is wrong. Therefore, an improved parameter estimation algorithm based on the combination of subband double frequency conjugation and LVT is proposed. The algorithm is constructed by constructing two subband signals with different central frequencies, The synthetic signal is obtained after the two signals are translated by conjugate multiplication. Finally, the synthetic signal is transformed by Keystone transform and LVT processing. The simulation and measured data processing results show that the algorithm can correct the distance migration of multiple targets at the same time and effectively reduce the computational complexity of the parameter search.
5, a parameter estimation algorithm based on piecewise Keystone transform and frequency domain LVT (SKT-FLVT) is proposed to estimate the parameters of moving targets without speed fuzzy in low signal to noise ratio. The algorithm first uses piecewise Keystone transform to correct linear distance migration, and then performs fast Fu Liye transformation on the azimuth of the echo data of each segment ( FFT) processing, and using the Keystone transform to adjust the frequency between the segments, and finally use the LVT processing to complete the parameter estimation. The Keystone transform and the LVT processing in this algorithm are easy to parallel computation, effectively improve the calculation efficiency and reduce the storage. The simulation results show that the algorithm can be used in the case of the unknown parameters of the moving target. Accurate estimation of the parameters is carried out directly.
6, the SKT-FLVT algorithm based on the fuzzy number estimation is proposed for the estimation of moving target parameters that have speed fuzzy. Firstly, the algorithm uses piecewise Keystone transform to correct linear distance migration, and then estimates the fuzzy number by one dimension search of the velocity fuzzy number. Then the echo data of each segment is FFT processed in azimuth and in the segment. The Keystone transform is used to adjust the frequency of frequency, and the parameter estimation is completed by LVT processing. The simulation and measured data processing results show that the proposed algorithm only needs one dimension search for the speed fuzzy number, and the accurate estimation results of the moving target parameters can be obtained at low SNR.
【学位授予单位】：北京理工大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN957.51
本文编号：2157217
[Abstract]:In order to improve the detection ability of modern radar for weak maneuvering target, it usually increases the signal to noise ratio before detection by increasing the accumulation time. However, due to the maneuvering characteristics of the target, the target is prone to distance migration and Doppler diffusion during the long time accumulation, which leads to the reduction of the traditional method of accumulation. Based on this, this paper studies the high speed machine. Moving target echo distance / Doppler migration correction method and parameter estimation algorithm for weak maneuvering target with long accumulation time.
The main contents of this paper are as follows:
1, the MDP-KTRFT parameter estimation algorithm is proposed for the distance migration and Doppler diffusion problem during the long time accumulation of the high speed maneuvering target in a single target scene. The algorithm uses the two order Keystone transform to correct the distance bending of the target echo envelope, and then uses the modified dechirping to estimate the target acceleration and compensate the target. The second phase of azimuth direction is used to realize the energy gathering of the target through the first-order RFT technique, and the high-precision estimation results of target motion parameters and initial distance are obtained.
2, the FrFT-KTRFT parameter estimation algorithm is proposed for the distance migration and Doppler diffusion problem during the long time accumulation of the high-speed maneuvering target in the multi-target scene. The algorithm first uses the two order Keystone transform to correct the distance bending of the target echo envelope, and then uses the fractional Fourier transform (FrFT) to estimate the target acceleration. The degree and compensation of the two phase of the direction of the target, and finally through the first order RFT technology to achieve the aggregation of the target energy and obtain the high precision motion parameters and the initial distance of multiple targets, the.MDP-KTRFT algorithm and the FrFT-KTRFT algorithm can effectively compensate the distance migration and time variation of the target under the premise of the unknown target motion information. The Doppler frequency can overcome the Doppler's fuzzy limit and obtain high parameter estimation precision. By comparing with the two order RFT algorithm, it can be seen that the two algorithms can still obtain accurate target parameter estimation results in the case of lower computation.
3, in view of the problem that the existing parameter estimation algorithms need to be searched and processed, a joint estimation algorithm based on Keystone transform and Lv 's Transform (LVT) is proposed. The algorithm does not need multiple iterative search, and can solve the problem of the traditional LVT estimation precision affected by the distance migration, and further deduce the problem. The threshold of the signal-to-noise ratio of the proposed algorithm is given.
4, considering that the frequency and frequency of the parameters corresponding to the high speed moving target may exceed the corresponding main value interval of the LVT estimator, the parameter estimation is wrong. Therefore, an improved parameter estimation algorithm based on the combination of subband double frequency conjugation and LVT is proposed. The algorithm is constructed by constructing two subband signals with different central frequencies, The synthetic signal is obtained after the two signals are translated by conjugate multiplication. Finally, the synthetic signal is transformed by Keystone transform and LVT processing. The simulation and measured data processing results show that the algorithm can correct the distance migration of multiple targets at the same time and effectively reduce the computational complexity of the parameter search.
5, a parameter estimation algorithm based on piecewise Keystone transform and frequency domain LVT (SKT-FLVT) is proposed to estimate the parameters of moving targets without speed fuzzy in low signal to noise ratio. The algorithm first uses piecewise Keystone transform to correct linear distance migration, and then performs fast Fu Liye transformation on the azimuth of the echo data of each segment ( FFT) processing, and using the Keystone transform to adjust the frequency between the segments, and finally use the LVT processing to complete the parameter estimation. The Keystone transform and the LVT processing in this algorithm are easy to parallel computation, effectively improve the calculation efficiency and reduce the storage. The simulation results show that the algorithm can be used in the case of the unknown parameters of the moving target. Accurate estimation of the parameters is carried out directly.
6, the SKT-FLVT algorithm based on the fuzzy number estimation is proposed for the estimation of moving target parameters that have speed fuzzy. Firstly, the algorithm uses piecewise Keystone transform to correct linear distance migration, and then estimates the fuzzy number by one dimension search of the velocity fuzzy number. Then the echo data of each segment is FFT processed in azimuth and in the segment. The Keystone transform is used to adjust the frequency of frequency, and the parameter estimation is completed by LVT processing. The simulation and measured data processing results show that the proposed algorithm only needs one dimension search for the speed fuzzy number, and the accurate estimation results of the moving target parameters can be obtained at low SNR.
【学位授予单位】：北京理工大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN957.51
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