雷達機動目標長時間積累信號處理算法研究
發(fā)布時間：2018-08-01 10:03
【摘要】：為提高現(xiàn)代雷達對微弱機動目標的探測能力，通常通過增加積累時間來提高檢測前信噪比。但是由于目標的機動運動特性，長時間積累過程中目標易發(fā)生距離徙動和多普勒擴散，導(dǎo)致傳統(tǒng)的積累方法效能降低�；诖耍疚难芯扛咚贆C動目標回波距離/多普勒徙動校正方法以及長積累時間下微弱機動目標的參數(shù)估計算法。 本文的主要研究內(nèi)容如下： 1、針對單目標場景下的高速機動目標在長時間積累過程中出現(xiàn)的距離徙動和多普勒擴散問題，提出了MDP-KTRFT參數(shù)估計算法。該算法利用二階Keystone變換校正目標回波包絡(luò)的距離彎曲，然后利用改進的dechirping估計目標加速度并補償目標方位向的二次相位，最后通過一階RFT技術(shù)實現(xiàn)目標的能量聚集并獲得高精度的目標運動參數(shù)和初始距離的估計結(jié)果。 2、針對多目標場景下的高速機動目標在長時間積累過程中出現(xiàn)的距離徙動和多普勒擴散問題，提出了FrFT-KTRFT參數(shù)估計算法。該算法首先利用二階Keystone變換校正目標回波包絡(luò)的距離彎曲，然后利用分數(shù)階傅里葉變換（FrFT）估計目標加速度并補償目標方位向的二次相位，最后通過一階RFT技術(shù)實現(xiàn)目標能量的聚集并獲得多個目標的高精度的運動參數(shù)和初始距離的估計結(jié)果。MDP-KTRFT算法和FrFT-KTRFT算法均能在目標運動信息未知的前提下有效補償目標的距離徙動和時變多普勒頻率，同時能夠克服多普勒模糊的限制，獲得高的參數(shù)估計精度。通過與二階RFT算法進行比較可看出，兩種算法在較低運算量的情況下仍能獲得精確的目標參數(shù)估計結(jié)果。 3、針對現(xiàn)有參數(shù)估計算法需進行搜索處理的問題，提出了一種基于Keystone變換和Lv’s Transform（LVT）的多目標運動參數(shù)聯(lián)合估計算法，該算法無需進行多次迭代搜索，同時能夠解決傳統(tǒng)LVT算法估計精度受距離徙動影響的問題，并進一步推導(dǎo)出了所提算法的信噪比門限。 4、考慮到高速運動目標的參數(shù)對應(yīng)的頻率和調(diào)頻率有可能超出LVT估計器相應(yīng)的主值區(qū)間，導(dǎo)致參數(shù)估計錯誤，為此提出了一種基于子帶雙頻共軛和LVT相結(jié)合的改進的參數(shù)估計算法。該算法通過構(gòu)造兩個具有不同中心頻率的子帶信號，并對這兩個信號平移后進行共軛相乘處理得到合成信號，最后對該合成信號進行Keystone變換和LVT處理。仿真和實測數(shù)據(jù)處理結(jié)果表明，該算法能夠同時對多個目標的距離徙動進行校正，有效降低了參數(shù)搜索的運算復(fù)雜度。 5、針對低信噪比下無速度模糊的運動目標參數(shù)估計問題，提出了一種基于分段Keystone變換和頻域LVT相結(jié)合的參數(shù)估計算法（SKT-FLVT）。該算法首先采用分段Keystone變換校正線性距離徙動，然后對各段回波數(shù)據(jù)在方位向進行快速傅立葉變換（FFT）處理，并在段間采用Keystone變換校正頻率走動，最后采用LVT處理完成參數(shù)估計。該算法中的Keystone變換與LVT處理均易于并行計算，有效提升了計算效率的同時降低了存儲量。仿真結(jié)果表明，該算法能夠在運動目標參數(shù)信息未知的情況下直接進行精確的參數(shù)估計。 6、對于存在速度模糊的運動目標參數(shù)估計問題，提出了基于模糊數(shù)估計的SKT-FLVT算法。該算法首先采用分段Keystone變換校正線性距離徙動，然后對速度模糊數(shù)進行一維搜索來估計模糊數(shù)，之后對各段回波數(shù)據(jù)在方位向進行FFT處理，，并在段間采用Keystone變換校正頻率走動，最后采用LVT處理完成參數(shù)估計。仿真和實測數(shù)據(jù)處理結(jié)果表明，所提算法僅需對速度模糊數(shù)進行一維搜索，即可在低信噪比下獲得精確的運動目標參數(shù)估計結(jié)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.
【學(xué)位授予單位】：北京理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN957.51
本文編號：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.
【學(xué)位授予單位】：北京理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN957.51
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