自適應技術在衛(wèi)星導航接收機抗干擾中的應用
發(fā)布時間：2018-12-16 16:19
【摘要】：衛(wèi)星導航接收機所處的干擾環(huán)境未知且隨時間變化,接收機必須具有一定的環(huán)境適應性以消除干擾捕獲信號。為使導航接收機對信號具有空間分辨能力,通常將自適應技術與陣列天線技術相結合,通過自適應調整天線陣列的權系數(shù),使導航接收機天線陣主波束指向期望信號,在干擾方向形成強衰減,也稱這種技術為自適應波束形成技術。本文將主要研究動態(tài)環(huán)境中衛(wèi)星導航接收機天線陣的自適應波束形成算法及FPGA實現(xiàn),包括以下三個方面:(1)對空域自適應天線陣分別在白噪聲和有色噪聲環(huán)境下的抗干擾能力進行定量分析。其結果是:對于具有M個天線陣的系統(tǒng),在高斯白噪聲環(huán)境下的信噪比改善值為10log(M);在已知信號到達角、信號及干擾的統(tǒng)計特性的理想條件下,有色噪聲環(huán)境中的信噪比改善度與高斯白噪聲環(huán)境下相當,說明自適應波束形成器能夠消除有色干擾。但由于實際系統(tǒng)采用樣本協(xié)方差近似真實協(xié)方差,降低了系統(tǒng)信噪比改善度。(2)對空時功率倒置(PI,Power Inversion)波束形成器的性能進行了系統(tǒng)評估,結果表明,空時功率倒置算法可消除多種類型干擾,但受簡單約束影響,干擾與信號臨近時,信干噪比(SINR,Signal to Interference and Noise Ratio)衰減嚴重。研究了閉環(huán)自適應權矢量計算方法,引用改進LMS算法——限定穩(wěn)定裕度歸一化最小均方差(SM-NLMS,Set Membership NLMS)算法基本形式,采用PI準則做約束得到限定穩(wěn)定裕度歸一化功率倒置(SM-NPI,Set Membership Normalized Power Inversion)算法。仿真結果表明,SM-NPI能夠在保持LMS小運算量特征的基礎上,改善收斂速度。因進一步提高波束形成器權矢量收斂速度的需要,研究了波束形成器的開環(huán)算法——維納濾波方法,為解決維納濾波矩陣運算量大問題,研究了維納濾波器的降維方法。仿真結果表明,采用多級維納濾波方法可以在滿足濾波器性能要求下降低矩陣運算維數(shù),采用相關相減多級維納濾波器可以進一步提高運算速度。(3)研究了自適應算法在FPGA中的實現(xiàn)方法,因LMS算法存在濾波、誤差計算、權值更新必須按序進行的缺陷,采用延時最小均方差算法(DLMS,Delay Least Mean Square)實現(xiàn)LMS的并行運算,結合SM-NPI權值更新方法,得到可在FPGA中實現(xiàn)的權值計算算法——D-SM-NPI。ModelSim仿真和硬件測試表明,本文設計的抗干擾算法能夠在壓制性干擾噪聲環(huán)境中捕獲衛(wèi)星信號。
[Abstract]:The jamming environment of the satellite navigation receiver is unknown and changes with time. The receiver must have a certain environmental adaptability to eliminate the interference acquisition signal. In order to make the navigation receiver have spatial resolution to the signal, the adaptive technique is usually combined with the array antenna technology. By adjusting the weight coefficient of the antenna array, the main beam of the antenna array of the navigation receiver is directed to the desired signal. Strong attenuation in the direction of interference is also known as adaptive beamforming. In this paper, the adaptive beamforming algorithm and FPGA implementation of antenna array of satellite navigation receiver in dynamic environment will be studied. It includes the following three aspects: (1) quantitative analysis of anti-jamming ability of spatial adaptive antenna array under white noise and colored noise respectively. The result is: for the system with M antenna array, the SNR improvement value under Gao Si white noise environment is 10log (M);. Under the ideal condition of known signal arrival angle, signal and interference statistical characteristics, the improvement of SNR in colored noise environment is similar to that in Gao Si white noise environment, which indicates that adaptive beamformer can eliminate colored interference. But because the sample covariance is used to approximate the real covariance, the improvement of SNR is reduced. (2) the performance of space-time power inversion (PI,Power Inversion) beamformer is systematically evaluated, and the results show that, Space-time power inversion algorithm can eliminate many types of interference, but it is affected by simple constraints. When the interference is approaching to the signal, the signal-to-noise ratio (SINR,Signal to Interference and Noise Ratio) attenuation is serious. The closed-loop adaptive weight vector calculation method is studied, and the modified LMS algorithm is used to normalize the minimum mean square error (SM-NLMS,Set Membership NLMS) of the restricted stability margin, which is the basic form of the SM-NLMS,Set Membership NLMS) algorithm. The restricted stability margin normalized power inversion (SM-NPI,Set Membership Normalized Power Inversion) algorithm is obtained by using PI criterion as constraint. The simulation results show that SM-NPI can improve the convergence speed on the basis of preserving the characteristics of LMS small computation. In order to improve the speed of weight vector convergence of beamformer, the open loop algorithm of beamformer, Wiener filter, is studied. In order to solve the problem of large computation of Wiener filter matrix, the dimension reduction method of Wiener filter is studied. The simulation results show that the multistage Wiener filtering method can reduce the computational dimension of the matrix when it meets the performance requirements of the filter. Using correlation subtractive multistage Wiener filter can further improve the operation speed. (3) the realization method of adaptive algorithm in FPGA is studied. Because of the defects of LMS algorithm, such as filtering, error calculation, weight updating must be carried out in order. Using the delay minimum mean square error algorithm (DLMS,Delay Least Mean Square) to realize the parallel operation of LMS and the SM-NPI weight updating method, the D-SM-NPI.ModelSim simulation and hardware test show that the algorithm can be implemented in FPGA. The anti-jamming algorithm designed in this paper can capture satellite signal in the environment of suppression jamming noise.
【學位授予單位】：西安建筑科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN965.5
本文編號：2382684
[Abstract]:The jamming environment of the satellite navigation receiver is unknown and changes with time. The receiver must have a certain environmental adaptability to eliminate the interference acquisition signal. In order to make the navigation receiver have spatial resolution to the signal, the adaptive technique is usually combined with the array antenna technology. By adjusting the weight coefficient of the antenna array, the main beam of the antenna array of the navigation receiver is directed to the desired signal. Strong attenuation in the direction of interference is also known as adaptive beamforming. In this paper, the adaptive beamforming algorithm and FPGA implementation of antenna array of satellite navigation receiver in dynamic environment will be studied. It includes the following three aspects: (1) quantitative analysis of anti-jamming ability of spatial adaptive antenna array under white noise and colored noise respectively. The result is: for the system with M antenna array, the SNR improvement value under Gao Si white noise environment is 10log (M);. Under the ideal condition of known signal arrival angle, signal and interference statistical characteristics, the improvement of SNR in colored noise environment is similar to that in Gao Si white noise environment, which indicates that adaptive beamformer can eliminate colored interference. But because the sample covariance is used to approximate the real covariance, the improvement of SNR is reduced. (2) the performance of space-time power inversion (PI,Power Inversion) beamformer is systematically evaluated, and the results show that, Space-time power inversion algorithm can eliminate many types of interference, but it is affected by simple constraints. When the interference is approaching to the signal, the signal-to-noise ratio (SINR,Signal to Interference and Noise Ratio) attenuation is serious. The closed-loop adaptive weight vector calculation method is studied, and the modified LMS algorithm is used to normalize the minimum mean square error (SM-NLMS,Set Membership NLMS) of the restricted stability margin, which is the basic form of the SM-NLMS,Set Membership NLMS) algorithm. The restricted stability margin normalized power inversion (SM-NPI,Set Membership Normalized Power Inversion) algorithm is obtained by using PI criterion as constraint. The simulation results show that SM-NPI can improve the convergence speed on the basis of preserving the characteristics of LMS small computation. In order to improve the speed of weight vector convergence of beamformer, the open loop algorithm of beamformer, Wiener filter, is studied. In order to solve the problem of large computation of Wiener filter matrix, the dimension reduction method of Wiener filter is studied. The simulation results show that the multistage Wiener filtering method can reduce the computational dimension of the matrix when it meets the performance requirements of the filter. Using correlation subtractive multistage Wiener filter can further improve the operation speed. (3) the realization method of adaptive algorithm in FPGA is studied. Because of the defects of LMS algorithm, such as filtering, error calculation, weight updating must be carried out in order. Using the delay minimum mean square error algorithm (DLMS,Delay Least Mean Square) to realize the parallel operation of LMS and the SM-NPI weight updating method, the D-SM-NPI.ModelSim simulation and hardware test show that the algorithm can be implemented in FPGA. The anti-jamming algorithm designed in this paper can capture satellite signal in the environment of suppression jamming noise.
【學位授予單位】：西安建筑科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN965.5
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