探地雷達(dá)回波相鄰道信號(hào)具有很大的相似性，本文利用相鄰道信號(hào)間的相關(guān)性，改
進(jìn)了二次樣條小波模極大值搜索算法，提出了一種基于信號(hào)相關(guān)性的奇異點(diǎn)檢測(cè)算法，并加以實(shí)現(xiàn)。實(shí)驗(yàn)結(jié)果表明改進(jìn)后的算法能夠進(jìn)一步去除噪聲產(chǎn)生的奇異點(diǎn)，更加準(zhǔn)確的判斷目標(biāo)回波的奇異點(diǎn)位置，為地下埋藏物位置的判斷提供有利的判據(jù)。
關(guān)鍵詞：小波變換，樣條小波，Lipschitz 指數(shù)，奇異性，探地雷達(dá)
Abstract： Based on the wavelet module maxima theory of Mallat and analyzing the
feature of the GPR’s echo wave signals in detail. Because the GPR echo wave
neighboring scan signals are similar, the paper utilizes the signal correlativity and
improves the wavelet module maxima algorithm. The result of experiments validates
the improved algorithm can wipe off the noise’s disturbance more efficiently and get
the exact positions of the singularities. It is important for showing the position of
object under the ground.
Key words: GPR, spline wavelet, Lipschitz exponent, singularity