基于貝塞爾函數(shù)基信號(hào)分解的微動(dòng)群目標(biāo)特征提取方法
doi: 10.11999/JEIT161036
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(61471386, 61571457)
Micro-Doppler Feature Extraction of Group Targets Using Signal Decomposition Based on Bessel Function Basis
Funds:
The National Natural Science Foundation of China (61471386, 61571457)
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摘要: 微動(dòng)特征提取是群目標(biāo)分辨的有效手段，以往針對(duì)孤立目標(biāo)的特征提取技術(shù)不再適用。針對(duì)此該文提出了一種基于信號(hào)分解的微動(dòng)群目標(biāo)特征提取方法。首先通過(guò)分析微動(dòng)信號(hào)的正弦調(diào)頻(SFM)形式，推導(dǎo)了SFM信號(hào)相位項(xiàng)在k-分辨率貝塞爾函數(shù)基上的分解結(jié)果；然后根據(jù)回波分解結(jié)果中微動(dòng)頻率與函數(shù)基的一一對(duì)應(yīng)關(guān)系進(jìn)行頻率粗略估計(jì)，并針對(duì)誤差產(chǎn)生原因給出了精確的微動(dòng)頻率估計(jì)方法；最后在離散信號(hào)相位解模糊的基礎(chǔ)上，完成各子目標(biāo)的微動(dòng)頻率提取。仿真實(shí)驗(yàn)驗(yàn)證了算法的有效性，且與正弦調(diào)頻傅里葉變換(SFMFT)算法和平均幅度差函數(shù)(AMDF)算法相比具有更高精度。
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關(guān)鍵詞:
- 微多普勒 /
- 群目標(biāo) /
- 貝塞爾函數(shù)基 /
- 特征提取 /
- 參數(shù)估計(jì)
Abstract: Micro-Doppler (m-D) feature extraction is significant for group target discrimination, while the methods for single target are invalid. An m-D feature extraction method of group targets is proposed based on signal orthogonal decomposition. First, the Sinusoidal Frequency-Modulated (SFM) form of m-D signals and the decomposition result of the phase term on k-resolution Bessel basis is deduced. The m-D frequency is coarsely estimated by the one-to-one relationship between frequencies and basis functions. Then an algorithm is introduced to reduce the error and thus a finer estimation is obtained. Finally, the m-D frequency of each target is extracted by discrete echoes without phase shift ambiguity. Simulation experiments validate the effectiveness, and show that the proposed method outperforms the Sinusoidal Frequency Modulation Fourier Transform (SFMFT)-based method and Average Magnitude Difference Function (AMDF)-based method in estimation precision.-
Key words:
- Micro-Doppler (m-D) /
- Group targets /
- Bessel function basis /
- Feature extraction /
- Parameter estimation
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