臺灣博碩士論文加值系統

隨著科技進步，隱形飛機和反輻射飛彈的出現，雷達面臨”四大威脅”，然而多態雷達能有效地對抗”四大威脅”，因此，有越來越多學者往多態雷達發展，一些應用於多態雷達的位置估測方法也已被提出，像訊號到達時間定位技術(TOA)、訊號到達角度(AOA)定位技術和結合訊號到達時間(TOA)和訊號到達角度(AOA)的定位技術。在傳統訊號到達時間(TOA)定位技術，是利用最小平方法(LS)來估測目標位置，當某接收站測量誤差遠大於其他接收站，會嚴重影響精確度。在本篇論文裡，我們提出一個演算法，目的是消除誤差較大的接收資料，只留下誤差較小的接收資料，再用最小平方法來估測目標位置，經電腦模擬結果，驗證了我們所提出的演算法其精確度高於傳統的訊號到達時間(TOA)定位技術。
此外，我們提出兩個定位方法，其一是在訊號到達角度(AOA)量測下，利用最小平方法(LS)去估測目標位置；另一方法是結合訊號到達時間(TOA)和訊號到達角度(AOA)，使用加權最小平方法(WLS)去估測目標位置，根據模擬結果，我們得知，接收站越多其精確度越高。

With scientific and technological progress in stealth aircraft and antiradiation missiles (ARM), there are four types of threats to radars. However, multistatic radar can resist these threats effectively. Therefore, an increasing number of researchers have developed multistatic radar over the past few years. Some estimation techniques for target location using the multistatic radar have been proposed, e.g. the time of arrival (TOA) position location (PL) technique, the angle of arrival (AOA) PL technique and a hybrid of the TOA and AOA PL techniques. The conventional TOA PL technique employs the least square (LS) method to estimate target location. When the measurement error of a certain receiver is far greater than the measurement error of other receivers (we call it great error), the location accuracy is seriously affected. In this thesis, we propose an algorithm to cancel the effect of great error. The performance measure on location estimation is the root mean square error (RMSE). Using simulation, we demonstrate that the proposed algorithm is superior to the conventional TOA algorithm.
We also propose two position algorithms. One of the proposed algorithms employs the LS method to estimate target location based on an AOA measurement. The other one employs the weighted least square (WLS) method to estimate the target location based on the TOA and AOA measurements. Based on the simulation results, we know that the root mean square error (RMSE) is reduced when the number of combined receivers is increased.

摘要……. i
Abstract… ii
Contents… iv
List of Figures vi
List of Tables vii
Chapter 1 Introduction 1
1.1 Background 1
1.2 Concept of Radar Operation 1
1.3 Radar Applications and Functions 2
1.4 Overview of Monostatic, Bistatic and Multistatic Radar 3
1.5 The Performance Measure 5
1.6 Organization of the Thesis 5
Chapter 2 Data Collection 7
2.1 TOA Measurement for Bistatic Radar 7
2.2 TOA Measurement for T2R Multistatic Radar 9
2.3 AOA Measurement 11
Chapter 3 Target Location Estimation Techniques: Principles and Algorithms 12
3.1 TOA PL Technique 12
3.2 AOA PL Technique 15
3.3 The Hybrid of TOA and AOA Techniques 18
Chapter 4 A Simple Method to Enhance the Accuracy of Multistatic Radar System Based on TOA PL Algorithm 20
4.1 The Proposed Algorithm for the TOA PL 20
4.2 Performance Evaluation 23
4.3 Simulation Results 24
Chapter 5 A Simple Position Algorithm for the Multistatic Radar System Based on the AOA Measurement 26
5.1 Basic Model 26
5.2 Proposed Algorithm (1) 27
5.3 Proposed Algorithm (2) 27
5.4 Performance Evaluation 29
Chapter 6 A Simple Position Algorithm for the Multistatic Radar System Base on the TOA and AOA Measurement 31
6.1 The Basic Model 31
6.2 The Propose Method for Hybrid of TOA/AOA PL Algorithm 32
6.3 The Performance Evaluation 34
6.4 Simulation Results 35
Chapter 7 Conclusions and Future Works 37
7.1 Conclusions 37
7.2 Future Works 38
Appendix A 39
References 42

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