Due to the inherent vulnerability of GNSS and the increasing complexity of the electromagnetic environment in recent years, GNSS signals are facing a growing threat from types of jamming interference. Early detection of GNSS interference is crucial to provide timely warnings before degradation in navigation and positioning functions occurs. This paper presents a novel approach for GNSS jamming interference detection using the statistical analysis, while also the influence of Automatic Gain Control (AGC) on detection is analyzed. By comparing the similarities of mean value derived from signals under normal and potential jamming conditions, hypothesis testing is introduced to detect the presence of jamming. The detection results are evaluated on Continuous Wave (CW), Chirp, and Additive White Gaussian Noise (AWGN) jamming signals by a semi-physical simulation platform. The results demonstrate that the approach exhibits a high detection rate under low JSR conditions.

Compressed sensing provides an elegant framework for recovering sparse signals from compressed measurements. This paper addresses the problem of sparse signal reconstruction from compressed measurements that is more robust to complex, especially non-Gaussian noise, which arises in many applications. For this purpose, we present a method that exploits the maximum negentropy theory to promote the adaptability to noise. This problem is formalized as a constrained minimization problem, where the objective function is the negentropy of measurement error with sparse constraint ${\ell }_p\left(0<p<1\right)$-norm. On the minimization issue of the problem, although several promising algorithms have been proposed in the literature, they are very computationally demanding and thus cannot be used in many practical situations. To improve on this, we propose an efficient algorithm based on a fast iterative shrinkage-thresholding algorithm that can converge fast. Both the theoretical analysis and numerical experiments show the better accuracy and convergent rate of the proposed method.