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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/6485

Title: 非穩態信號之雜訊經驗模型偵測技術
Techniques of Non-Stationary Signal Detection based on the Empirical Model of Noise
Authors: Fu-Tai Wang
王復台
Contributors: NTOU:Department of Electrical Engineering
國立臺灣海洋大學:電機工程學系
Keywords: 非穩態信號;信號偵測;雜訊經驗模型;小波轉換;希爾伯特-黃轉換
Non-Stationary Signal;Signal Detection;Empirical Model of Noise;Wavelet Transformation;Hilbert-Huang transformation
Date: 2006
Issue Date: 2011-06-22T08:52:12Z
Abstract: 本研究主要目的在於偵測何時有不同於水下環境之潛在信號的出 沒。有些方法針對特殊情況採用特定的模型。有的則利用離散小波轉 換(DWT)對於信號有無所產生之不同的概要特性,形成一個能辨別信 號的雜訊經驗模型。本論文將採用其他非穩態訊號處理方法取代離散 小波轉換,以提高偵測性能。 強健離散小波轉換將取代離散小波轉換以偵測水下多路徑信號。 利用離散小波轉換中的比例函數,在ZAK 域中做迭代,產生強健離散 小波轉換。此強健離散小波轉換所建立之水下背景雜訊的遞迴密度估 測,其偵測多路徑信號的能力,比使用離散小波轉換來得提高。 移位不變雙樹離散小波轉換(DT DWT)雜訊模型是基於移位不變 雙樹離散小波轉換所建立。多路徑環境下,移位不變雙樹離散小波轉 換所建立的多解析子空間可以保持更多的小波係數能量。利用接收器 操作特性(ROC)曲線可得出雙樹離散小波轉換偵測器與離散小波轉換 偵測器的偵測性能比較。 希爾伯特-黃轉換(HHT)裡的經驗樣式拆解(EMD)將用於偵測水 下信號。任何輸入信號在經驗樣式拆解之下,可產生少量之具有完備 性、幾乎正交性、區域性與適應性之可作為該非穩態信號基底的本質 樣式函數(IMF)。經電腦模擬,以接收器操作特性(ROC)曲線分析可得 知經驗樣式拆解偵測器比離散小波轉換偵測器具有更好的偵測性能。 最後本論文提出利用小波包法提高希爾伯特-黃轉換估測信號之 瞬時頻率(IF)的能力。
The primary interest here is in the determination of when a potential signal appears in an underwater environment. Many approaches involve predefined models that are designed for particular situations. Some summary features of the Discrete Wavelet Transform (DWT) decompositions of the noise can be used for identifying the signal. This dissertation attempts to use different non-stationary signal processing methods other than DWT in the empirical noise model to improve the detecting performance. A robust DWT is adopted as a solution to detect a multipath signal in the underwater environment. With an iterative algorithm in the Zak domain, a scaling function can be turned to the robust one. By utilizing the robust DWT reconstruction to establish the recursive density estimator of the underwater background noise, the ability of detecting a multipath signal in the underwater environment is improved compared to that by using the DWT's. Based on shift invariant Dual-Tree Discrete Wavelet Transform (DT DWT), shift invariant DT DWT noise model is designed. In a multipath environment, this shift invariant DT DWT can generate multi-resolution subspaces that keep more of their coefficient energy in each of these subspaces. The detecting performance comparison using the receiver operating characteristics (ROC) curves of this proposed DT DWT-based detector and DWT-based method is presented. The empirical mode decomposition (EMD) of the Hilbert-Huang transformation (HHT) is introduced to the problem of signal detection in underwater sound. From the computer simulation, based on the ROC, a performance comparison shows that this proposed EMD-based detector is better than the DWT-based method. Finally, a wavelet packet based method to increase the ability of instantaneous frequency (IF) estimation of signals of the Hilbert-Huang transformation (HHT) is proposed.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0D88530002
http://ntour.ntou.edu.tw/ir/handle/987654321/6485
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