Effect of Colored Noise on STAP Algorithm for GNSS Anti-jamming and Algorithm Improvement
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摘要: 在全球卫星导航(GNSS)阵列天线抗干扰理论中，系统噪声通常被视为理想白噪声(AWGN)。但在实际工程中发现系统噪声通常是有色噪声且会影响空时自适应处理(STAP)算法的性能。该文首先推导得出了有色噪声功率谱与空时抗干扰后卫星导航信号相关峰的理论关系，然后通过仿真实验验证了该理论关系的正确性，同时分析了噪声功率谱的等效带宽和谱峰偏移对相关峰的影响，最后发现噪声功率谱能量越集中于卫星导航信号的功率谱谱峰处，空时抗干扰后的卫星导航信号相关峰衰减越大。针对上述问题，该文提出了对角加载和子空间投影方法，两种方法通过对噪声协方差矩阵的特征值进行一致化处理实现有色噪声的白化，从而消除了有色噪声的影响。最后通过仿真实验验证了所提方法的有效性。Abstract: In adaptive array processing for Global Navigation Satellite System (GNSS) anti-jamming, system noise is usually modeled as AWGN(Additive White Gauss Noise). But in engineering, system noise is generally non-white and colored noise has a great impact on the performance of STAP (Space-Time Adaptive Processing) algorithm. Firstly, the theoretical relationship between the power spectrum of noise and the correlation peak of GNSS signal after space-time anti-jamming is derived, then the theoretical relationship is verified by simulation experiment which simultaneously analyzes the effect of equivalent bandwidth and spectrum peak shift of noise on GNSS signal’s correlation peak. Experimental results show the more the noise power spectrum energy is concentrated at the peak of the power spectrum of GNSS signal, the lower the correlation peak of the GNSS signal after space-time anti-jamming. For the above problem, diagonal loading and subspace projection methods are proposed in this paper, and the two methods achieve the whitening of colored noise by consistent processing of the eigenvalues of the noise covariance matrix, so that the effect of colored noise is eliminated. Finally, method is verified by experiments.
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Key words:
- GNSS /
- Space-Time Adaptive Processing (STAP) /
- Colored noise /
- Effect analysis /
- Algorithm improvement
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