多項式相位信號時差估計方法
發(fā)布時間：2018-12-28 19:51
【摘要】：隨著現(xiàn)代通信行業(yè)的飛速發(fā)展,無線定位技術(shù)滲透到了我們?nèi)粘Ｉ畹姆椒矫婷�。通信服�?wù)、定位追蹤、信息安全等正成為當(dāng)今無線定位技術(shù)的重要發(fā)展方向并愈發(fā)影響和改變著人類的工作和生活。無線定位技術(shù)本質(zhì)是通過對基站與移動站之間傳輸信號的某一個或多個特征參數(shù)制定對應(yīng)的算法來實現(xiàn)對于位置坐標(biāo)的估計與獲取。AOA、TOA、SOA、TDOA定位方法構(gòu)成各自的定位體系,其中TDOA以其獨特的優(yōu)勢得到了越來越多的重視。而在很多現(xiàn)實應(yīng)用中,許多信號往往為非平穩(wěn)信號,且其相位也具有連續(xù)特性,那么常用的廣義互相關(guān)等基于平穩(wěn)特性信號的方法將不再適用�，F(xiàn)代信號處理中廣泛涵蓋的非線性、非平穩(wěn)問題中信號模型都可以用多項式相位信號來近似。本文主要針對多項式相位信號的時差估計問題,基于不同階數(shù)的多項式相位信號時差估計進(jìn)行算法研究。主要內(nèi)容有:1.研究了基于循環(huán)相關(guān)矩方法,將其幅度以及相位信息應(yīng)用于線性調(diào)頻信號時差估計方法,與傳統(tǒng)廣義互相關(guān)時差估計方法進(jìn)行了比較,明確了其對于處理非平穩(wěn)信號時差問題的優(yōu)勢。2.研究了分?jǐn)?shù)階傅里葉變換(FrFT)及基于FrFT的單分量/多分量線性調(diào)頻信號時差估計方法,并仿真驗證了其較好的估計性能。3.針對FrFT存在的偽峰干擾問題,引入了線性變換得到簡化分?jǐn)?shù)階傅里葉變換消除偽峰干擾并應(yīng)用于單分量/多分量線性調(diào)頻信號時差估計中,與傳統(tǒng)廣義互相關(guān)方法進(jìn)行了仿真比較并驗證了其在各種信號環(huán)境中的良好估計性能。4.提出了基于SFFT的線性調(diào)頻信號快速時差估計,利用預(yù)判法大幅度減小了二維搜索范圍從而降低了計算量。通過仿真比較了其與常規(guī)方法以及GCC方法估計效果,驗證了其在低信噪比環(huán)境下的良好估計性能。5.針對三階相位信號引入了信號的瞬時相關(guān)量將相位降為二階再利用上述二階相關(guān)方法進(jìn)行常規(guī)估計和快速估計,提取時差信息。仿真比較了其與傳統(tǒng)廣義互相關(guān)估計方法的效果,驗證了瞬時相關(guān)量對于處理三階相位信號時差問題的有效性和相關(guān)算法的穩(wěn)健性。
[Abstract]:With the rapid development of modern communication industry, wireless positioning technology permeates every aspect of our daily life. Communication services, location tracking, information security and so on are becoming the important development direction of wireless location technology and increasingly affecting and changing the work and life of human beings. The essence of wireless location technology is to estimate and obtain the position coordinates by making corresponding algorithm for one or more characteristic parameters of the signal transmitted between the base station and the mobile station. AOA,TOA,SOA, TDOA positioning methods constitute their respective positioning systems, in which TDOA has been paid more and more attention for its unique advantages. However, in many practical applications, many signals are often non-stationary signals, and their phases also have continuous characteristics, so the commonly used methods based on stationary signals such as generalized cross-correlation will no longer be applicable. In modern signal processing, nonlinear and nonstationary signal models can be approximated by polynomial phase signals. In this paper, the time difference estimation of polynomial phase signal is studied based on the different order of polynomial phase signal. The main contents are: 1. Based on the cyclic correlation moment method, the amplitude and phase information is applied to the time difference estimation of LFM signals, which is compared with the traditional generalized cross-correlation time difference estimation method. The advantages of this method in dealing with the non-stationary signal moveout problem are clarified. 2. The method of time difference estimation for single-component / multi-component LFM signals based on fractional Fourier transform (FrFT) and FrFT is studied. In order to solve the problem of pseudo peak interference in FrFT, the simplified fractional Fourier transform is introduced to eliminate the pseudo peak interference and is applied to the time difference estimation of single / multi-component LFM signals. The simulation results are compared with those of the traditional generalized cross-correlation method and its good estimation performance in various signal environments is verified. 4. The fast time difference estimation of LFM signal based on SFFT is presented. The 2-D search range is greatly reduced by using the prejudgment method and the computational complexity is reduced. The performance of the proposed method is compared with that of the conventional method and the GCC method by simulation, and its good performance is verified in low SNR environment. For the third order phase signal, the instantaneous correlation is introduced to reduce the phase to the second order and then the conventional and fast estimation is carried out by using the second-order correlation method mentioned above, and the time difference information is extracted. The simulation results show that the instantaneous correlation is effective and robust in dealing with the third order phase signal time difference problem.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN911.23
，
本文編號：2394360
[Abstract]:With the rapid development of modern communication industry, wireless positioning technology permeates every aspect of our daily life. Communication services, location tracking, information security and so on are becoming the important development direction of wireless location technology and increasingly affecting and changing the work and life of human beings. The essence of wireless location technology is to estimate and obtain the position coordinates by making corresponding algorithm for one or more characteristic parameters of the signal transmitted between the base station and the mobile station. AOA,TOA,SOA, TDOA positioning methods constitute their respective positioning systems, in which TDOA has been paid more and more attention for its unique advantages. However, in many practical applications, many signals are often non-stationary signals, and their phases also have continuous characteristics, so the commonly used methods based on stationary signals such as generalized cross-correlation will no longer be applicable. In modern signal processing, nonlinear and nonstationary signal models can be approximated by polynomial phase signals. In this paper, the time difference estimation of polynomial phase signal is studied based on the different order of polynomial phase signal. The main contents are: 1. Based on the cyclic correlation moment method, the amplitude and phase information is applied to the time difference estimation of LFM signals, which is compared with the traditional generalized cross-correlation time difference estimation method. The advantages of this method in dealing with the non-stationary signal moveout problem are clarified. 2. The method of time difference estimation for single-component / multi-component LFM signals based on fractional Fourier transform (FrFT) and FrFT is studied. In order to solve the problem of pseudo peak interference in FrFT, the simplified fractional Fourier transform is introduced to eliminate the pseudo peak interference and is applied to the time difference estimation of single / multi-component LFM signals. The simulation results are compared with those of the traditional generalized cross-correlation method and its good estimation performance in various signal environments is verified. 4. The fast time difference estimation of LFM signal based on SFFT is presented. The 2-D search range is greatly reduced by using the prejudgment method and the computational complexity is reduced. The performance of the proposed method is compared with that of the conventional method and the GCC method by simulation, and its good performance is verified in low SNR environment. For the third order phase signal, the instantaneous correlation is introduced to reduce the phase to the second order and then the conventional and fast estimation is carried out by using the second-order correlation method mentioned above, and the time difference information is extracted. The simulation results show that the instantaneous correlation is effective and robust in dealing with the third order phase signal time difference problem.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN911.23
，
本文編號：2394360
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