- 學位論文
應用小波轉換於雷達訊號週期與特徵分析之實務研究
The Practical Aspect of Wavelet Basis in Analysis of Period and Characteristics of Radar Signal
摘要
雷達訊號辨識亦可稱為特殊射源辨識或獨特訊號辨識。早期與實務有關之討論中，相關預警參數包含有頻率（Frequency）、脈波來復頻（Pulse Repetition Frequency）、脈波寬（Pulse Width）、掃描形式（Scan type）、掃描時間（Scan time）、掃描率（Scan rate）、測向（Direction Finding）等。 對於同時出現且具有相同參數特徵之雷達訊號，以目前之分析方式而言，無法滿足軍方戰術需求，尤其是相同款式之發射源。現以小波轉換為思考基礎，提供一個新的分析模式以支持並提昇分析能量。經由改變時間軸之量度以解析訊號，進而以小波轉換的特點為新角度來觀察及辨識雷達訊號，比較此新分析架構所重組之結果，顯示個人所提出的改善方案，的確在未來的雷達訊號辨識能有所助益。 論文主要之研究目的，係著眼於尋求在最經濟的情況下，為分析雷達訊號建構不同之分析模式，對提昇現有設備之弁遄A可獲致最佳研析效益。由於個人電腦之性能已較數年前大有提昇，其成本遠比UNIX-OS之工作站低廉釵h，同時在不改變現行作業模式與投入過多改善成本之前提下，將既有的分析架構加入小波轉換，以強化對雷達訊號之辨識度，經由模擬與實際訊號的實驗證明，小波轉換對大部分訊號的確能展現其背景特徵與訊號特性。
並列摘要
Radar Signal Identification is also termed Specific Emitter Identification (SEI), or Unique Signal Identification (USI). The discussions related to this practical aspect of technique in early stages, the threaten parameters used included Frequency, Pulse Repetition Frequency (PRF), Pulse width (PW), Scan type, Sweep time, Scan rate, Direction Finding (DF) etc. Currently analysis could not satisfy army tactical requirement when two radar’s signal be received with pretty similar parameters, especially identify two same model radar’s emitter. A new ideal based on wavelet transform offers different method to support and enhance the analysis ability. By changing time domain’s scale to deconstruct the signal, and then observe and identify radar signal in a new angle with wavelet transformed particularity. Compared the results that reconstructed by new analysis architecture, it indicate the better solution we proposed that will help radar signal identification. The main purpose of the thesis is to construct a different analyzed model for radar signal analysis which can obtain the best benefit in improving the performance of current system under the most economical situation. Due to the capability of personal computer is far ahead improved than several years ago; its price cost is also far less than the workstation which worked with UNIX-OS. In a presupposition of not to change the operating method in hand and to put in too much reformation cost, we join the wavelet transform into analysis structure in existence to strengthen the ability in identifying radar signals. The experiment was proved by simulating and real signals, that wavelet transform may unroll the background features and signal’s characters in the majority of signals.
參考文獻
延伸閱讀
- 倪勝火、張裕（2021）。複數連續小波轉換應用於透地雷達信號之分析。中國土木水利工程學刊，33(2)，105-118。https://doi.org/10.6652/JoCICHE.202104_33(2).0003
- Huang, R. J. (2006). 小波轉換應用於語音訊號處理之研究 [master's thesis, Tatung University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0081-0607200917235767
- 黃丁威（2009）。以對稱小波轉換演算法應用於移動物件偵測與追蹤之研究〔碩士論文，淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2009.00694
- Chang, C. C., Chang, S. M., Huang, H. Y., & Yeh, J. Y. (2008). 應用小波轉換於應變能損害偵測方法之研究. 機械技師學刊, 1(1), 23-26. https://doi.org/10.6208/JPME-2008-01-04
- 張安邦（2017）。Wavelet transform in warning signal detection and analysis of blood pressure and pulse signal〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU201700279