基于分?jǐn)?shù)階傅里葉變換的Chirp淺剖精細(xì)探測方法
doi: 10.11999/JEIT140140 cstr: 32379.14.JEIT140140
基金項(xiàng)目:
國家國際科技合作項(xiàng)目(2008DFR70320)，國家自然科學(xué)基金 (41327004, 41306182, 61401112)，教育部博士點(diǎn)基金 (20112304130003)和哈爾濱市科技攻關(guān)項(xiàng)目(2008AA2AE005)資助課題
Chirp Sub-bottom Profiling Detailed Detection Method Based on Fractional Fourier Transform
-
摘要: 實(shí)現(xiàn)弱回波信號檢測和高信噪比(SNR)淺剖圖像獲取是淺剖精細(xì)探測的首要任務(wù)。該文在分析分?jǐn)?shù)階傅里葉變換(FrFT)解卷積原理，推導(dǎo)時(shí)間量綱化變換公式的基礎(chǔ)上，提出一種基于FrFT的淺剖精細(xì)探測新方法。該方法通過FrFT解卷積實(shí)現(xiàn)分?jǐn)?shù)階傅里葉域(u域)沉積層沖激響應(yīng)求解，采用u域加窗濾波技術(shù)對帶內(nèi)噪聲進(jìn)行有效抑制，經(jīng)時(shí)間量綱化變換實(shí)現(xiàn)高信噪比u域沉積層沖激響應(yīng)包絡(luò)信號至?xí)r域淺剖包跡的直接變換，得到高質(zhì)量的淺剖圖像。仿真實(shí)驗(yàn)和實(shí)測數(shù)據(jù)處理驗(yàn)證了算法的精細(xì)探測能力，算法性能優(yōu)于脈沖壓縮和自回歸(AR)預(yù)測濾波方法。
-
關(guān)鍵詞:
- 信號處理 /
- 淺地層剖面 /
- 精細(xì)探測 /
- 分?jǐn)?shù)階傅里葉變換 /
- 帶內(nèi)噪聲抑制 /
- 時(shí)間量綱化變換
Abstract: Weak signal detection and high SNR seismic image generation are primary tasks in detailed sub-bottom profile detection. After analyzing the principle of deconvolution based on Fractional Fourier Transform (FrFT) and deriving the formula of time dimensional transformation, a new detailed sub-bottom profile detection algorithm based on FrFT is proposed. The fractional Fourier domain (u domain) sub-bottom impulse response is achieved by u domain deconvolution and the intraband SNR is increased by u domain windowed filtering technique, then high SNR envelop of u domain sediment impulse response envelop is transformed to time domain by time dimensional transformation to get high quality sub-bottom profile. Simulation and experimental data processing validate the validity of the algorithm in intraband denoising and detailed detection, and its performance is better than pulse compression and AutoRegressive (AR) forecast filtering. -
計(jì)量
- 文章訪問數(shù): 2469
- HTML全文瀏覽量: 153
- PDF下載量: 608
- 被引次數(shù): 0
下載:
