與主動雷達系統不同，被動雷達系統僅需專屬接收機，即可偵測空中目標物，本論文基於雙站被動式雷達系統架構下，為了偵測未知目標物，結合到達角度法(AOA)與到達時差法(TDOA)的資訊。利用多重訊號分辨演算法(MUSIC)估測目標物角度(AOA)，再配合模稜函數(Ambiguity function)估測出目標物的距離(TDOA)與都普勒偏移，結合以上3個參數可定位出目標物的位置。
本論文包含硬體實作與軟體模擬兩部份；硬體實作部份，利用LYRTECH所開發之軟體無線電平台實現多重訊號分辨演算法，並使用最小平方法(least square method) 補償由射頻前端模組所造成的相位與增益。
模擬方面，首先，模擬在數位電視訊號下之模稜函數，此函數因數位電視訊號內引導訊號與保護區間而產生干擾峰值。為了改善模稜函數精準度，本論文消除這些干擾峰值；同時，加入窗型技術以抑制模稜函數旁波。接下來本論文提出利用波束形成技術(beamforming)與最小平方法在多目標物情況下可對應角度、距離、都普勒偏移3個參數。模擬結果顯示，此參數對應方式在多目標物時可有效的決定目標物的位置。

Unlike an active radar system, a passive radar system only requires a dedicate receiver end to detect airborne targets. To locate the unknown targets, we jointly combine Angle-of-Arrival and Time-Different-of-Arrival information. In this work, we use Multiple Signal Classification algorithm to estimate angle of arrival information of targets, and use ambiguity function to detect targets ranges and Doppler shifts in a bistatic passive radar system. Combining these parameters, we can locate positions of targets.
This thesis contains hardware implementation and software simulations. In hardware implementation, we use LYRTECH’s Software Defined Radio platform to implement Multiple Signal Classification algorithm, and use the least square method to compensate the phase and gain caused by RF front-end.
In simulations, we first simulate an ambiguity function for digital video broadcasting terrestrial signal, which results in unwanted deterministic peaks due to the guard interval and the pilots in the digital video broadcasting terrestrial passive radar. In order to improve the accuracy of ambiguity function, we remove these unwanted peaks; in the meantime, we also apply a window function to further reduce the ambiguity function sidelobes. Second, we propose a method using beamforming technique and least square method to mapping angles, ranges, and Doppler shifts for multiple airborne targets. Simulation results shows that the proposed mapping scheme can effectively determine positions of multiple targets.

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