雷達(dá)機(jī)動(dòng)目標(biāo)長(zhǎng)時(shí)間積累信號(hào)處理算法研究
發(fā)布時(shí)間：2018-08-01 10:03
【摘要】：為提高現(xiàn)代雷達(dá)對(duì)微弱機(jī)動(dòng)目標(biāo)的探測(cè)能力，通常通過增加積累時(shí)間來提高檢測(cè)前信噪比。但是由于目標(biāo)的機(jī)動(dòng)運(yùn)動(dòng)特性，長(zhǎng)時(shí)間積累過程中目標(biāo)易發(fā)生距離徙動(dòng)和多普勒擴(kuò)散，導(dǎo)致傳統(tǒng)的積累方法效能降低�；诖�，本文研究高速機(jī)動(dòng)目標(biāo)回波距離/多普勒徙動(dòng)校正方法以及長(zhǎng)積累時(shí)間下微弱機(jī)動(dòng)目標(biāo)的參數(shù)估計(jì)算法。 本文的主要研究?jī)?nèi)容如下： 1、針對(duì)單目標(biāo)場(chǎng)景下的高速機(jī)動(dòng)目標(biāo)在長(zhǎng)時(shí)間積累過程中出現(xiàn)的距離徙動(dòng)和多普勒擴(kuò)散問題，提出了MDP-KTRFT參數(shù)估計(jì)算法。該算法利用二階Keystone變換校正目標(biāo)回波包絡(luò)的距離彎曲，然后利用改進(jìn)的dechirping估計(jì)目標(biāo)加速度并補(bǔ)償目標(biāo)方位向的二次相位，最后通過一階RFT技術(shù)實(shí)現(xiàn)目標(biāo)的能量聚集并獲得高精度的目標(biāo)運(yùn)動(dòng)參數(shù)和初始距離的估計(jì)結(jié)果。 2、針對(duì)多目標(biāo)場(chǎng)景下的高速機(jī)動(dòng)目標(biāo)在長(zhǎng)時(shí)間積累過程中出現(xiàn)的距離徙動(dòng)和多普勒擴(kuò)散問題，提出了FrFT-KTRFT參數(shù)估計(jì)算法。該算法首先利用二階Keystone變換校正目標(biāo)回波包絡(luò)的距離彎曲，然后利用分?jǐn)?shù)階傅里葉變換（FrFT）估計(jì)目標(biāo)加速度并補(bǔ)償目標(biāo)方位向的二次相位，最后通過一階RFT技術(shù)實(shí)現(xiàn)目標(biāo)能量的聚集并獲得多個(gè)目標(biāo)的高精度的運(yùn)動(dòng)參數(shù)和初始距離的估計(jì)結(jié)果。MDP-KTRFT算法和FrFT-KTRFT算法均能在目標(biāo)運(yùn)動(dòng)信息未知的前提下有效補(bǔ)償目標(biāo)的距離徙動(dòng)和時(shí)變多普勒頻率，同時(shí)能夠克服多普勒模糊的限制，獲得高的參數(shù)估計(jì)精度。通過與二階RFT算法進(jìn)行比較可看出，兩種算法在較低運(yùn)算量的情況下仍能獲得精確的目標(biāo)參數(shù)估計(jì)結(jié)果。 3、針對(duì)現(xiàn)有參數(shù)估計(jì)算法需進(jìn)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(biāo)運(yùn)動(dòng)參數(shù)聯(lián)合估計(jì)算法，該算法無需進(jìn)行多次迭代搜索，同時(shí)能夠解決傳統(tǒng)LVT算法估計(jì)精度受距離徙動(dòng)影響的問題，并進(jìn)一步推導(dǎo)出了所提算法的信噪比門限。 4、考慮到高速運(yùn)動(dòng)目標(biāo)的參數(shù)對(duì)應(yīng)的頻率和調(diào)頻率有可能超出LVT估計(jì)器相應(yīng)的主值區(qū)間，導(dǎo)致參數(shù)估計(jì)錯(cuò)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(jìn)的參數(shù)估計(jì)算法。該算法通過構(gòu)造兩個(gè)具有不同中心頻率的子帶信號(hào)，并對(duì)這兩個(gè)信號(hào)平移后進(jìn)行共軛相乘處理得到合成信號(hào)，最后對(duì)該合成信號(hào)進(jìn)行Keystone變換和LVT處理。仿真和實(shí)測(cè)數(shù)據(jù)處理結(jié)果表明，該算法能夠同時(shí)對(duì)多個(gè)目標(biāo)的距離徙動(dòng)進(jìn)行校正，有效降低了參數(shù)搜索的運(yùn)算復(fù)雜度。 5、針對(duì)低信噪比下無速度模糊的運(yùn)動(dòng)目標(biāo)參數(shù)估計(jì)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(jì)算法（SKT-FLVT）。該算法首先采用分段Keystone變換校正線性距離徙動(dòng)，然后對(duì)各段回波數(shù)據(jù)在方位向進(jìn)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(dòng)，最后采用LVT處理完成參數(shù)估計(jì)。該算法中的Keystone變換與LVT處理均易于并行計(jì)算，有效提升了計(jì)算效率的同時(shí)降低了存儲(chǔ)量。仿真結(jié)果表明，該算法能夠在運(yùn)動(dòng)目標(biāo)參數(shù)信息未知的情況下直接進(jìn)行精確的參數(shù)估計(jì)。 6、對(duì)于存在速度模糊的運(yùn)動(dòng)目標(biāo)參數(shù)估計(jì)問題，提出了基于模糊數(shù)估計(jì)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(dòng)，然后對(duì)速度模糊數(shù)進(jìn)行一維搜索來估計(jì)模糊數(shù)，之后對(duì)各段回波數(shù)據(jù)在方位向進(jìn)行FFT處理，，并在段間采用Keystone變換校正頻率走動(dòng)，最后采用LVT處理完成參數(shù)估計(jì)。仿真和實(shí)測(cè)數(shù)據(jù)處理結(jié)果表明，所提算法僅需對(duì)速度模糊數(shù)進(jìn)行一維搜索，即可在低信噪比下獲得精確的運(yùn)動(dòng)目標(biāo)參數(shù)估計(jì)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(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.51
本文編號(hào)：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(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.51
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 姬國(guó)良;雷達(dá)反隱身技術(shù)發(fā)展探討[J];電子科技導(dǎo)報(bào);1994年03期
2 酈能敬;雷達(dá)反對(duì)抗的新領(lǐng)域 反隱身飛機(jī)與對(duì)抗反雷達(dá)導(dǎo)彈[J];電子學(xué)報(bào);1987年02期
3 王根原;保錚;;逆合成孔徑雷達(dá)運(yùn)動(dòng)補(bǔ)償中包絡(luò)對(duì)齊的新方法[J];電子學(xué)報(bào);1998年06期
4 王俊,張守宏;微弱目標(biāo)積累檢測(cè)的包絡(luò)移動(dòng)補(bǔ)償方法[J];電子學(xué)報(bào);2000年12期
5 張順生,曾濤;基于keystone變換的微弱目標(biāo)檢測(cè)[J];電子學(xué)報(bào);2005年09期
6 宋慧波;高梅國(guó);田黎育;毛二可;顧文彬;;一種基于動(dòng)態(tài)規(guī)劃法的雷達(dá)微弱多目標(biāo)檢測(cè)方法[J];電子學(xué)報(bào);2006年12期
7 周良臣;楊建宇;唐斌;;一種高效的LFM信號(hào)參數(shù)估計(jì)方法及性能分析[J];電子學(xué)報(bào);2007年06期
8 李濤;吳嗣亮;曾海彬;侯舒娟;;基于動(dòng)態(tài)規(guī)劃的雷達(dá)檢測(cè)前跟蹤新算法[J];電子學(xué)報(bào);2008年09期
9 胥嘉佳;劉渝;鄧振淼;;LFM信號(hào)參數(shù)估計(jì)的牛頓迭代方法初始值研究[J];電子學(xué)報(bào);2009年03期
10 王琨,羅琳;ISAR成象中包絡(luò)對(duì)齊的幅度相關(guān)全局最優(yōu)法[J];電子科學(xué)學(xué)刊;1998年03期
相關(guān)博士學(xué)位論文 前2條
1 李文臣;高速機(jī)動(dòng)目標(biāo)雷達(dá)信號(hào)參數(shù)估計(jì)與成像處理[D];國(guó)防科學(xué)技術(shù)大學(xué);2009年
2 易偉;基于檢測(cè)前跟蹤技術(shù)的多目標(biāo)跟蹤算法研究[D];電子科技大學(xué);2012年
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