A Spoofing Detection Algorithm Based on Coprime Array for GNSS Receiver

DOA Estimation under GNSS Spoofing Attacks Using a Coprime Array: From a Sparse Reconstruction Viewpoint

“…Although better DOA estimation performance can be achieved by combining virtual array interpolation and error compensation, it comes with an increase in computational complexity in the algorithm. Compared with existing methods in [6,8,12], the additional computation introduced in our approach mainly focuses on three operations: virtual array interpolation, signal-sparse reconstruction and off-grid error compensation. Virtual array interpolation technology needs to recover the Toeplitz covariance matrix, and its 3 .…”

“…Therefore, it seems that a sparse array might also be beneficial for improving the estimation performance of GNSS signal parameters. Inspired by this, in earlier works we proposed an underdetermined DOA estimation technology based on the sparse coprime array for GNSS signals, where the achievable DOFs could be increased by deriving an extended virtual array [12]. Nevertheless, the scheme in [12] fails to make full use of all the elements contained in the virtual array, which dramatically affects the estimation performance under a spoofing attack.…”

“…Inspired by this, in earlier works we proposed an underdetermined DOA estimation technology based on the sparse coprime array for GNSS signals, where the achievable DOFs could be increased by deriving an extended virtual array [12]. Nevertheless, the scheme in [12] fails to make full use of all the elements contained in the virtual array, which dramatically affects the estimation performance under a spoofing attack. In addition, the DOA estimation problems in [6,8,12] were solved by classical subspace-based methods; they required the number of incident signals to be prespecified or estimated [13].…”

“…Nevertheless, the scheme in [12] fails to make full use of all the elements contained in the virtual array, which dramatically affects the estimation performance under a spoofing attack. In addition, the DOA estimation problems in [6,8,12] were solved by classical subspace-based methods; they required the number of incident signals to be prespecified or estimated [13]. In this sense, it is of great importance to achieve better DOA estimation performance in the GNSS spoofing environment without using the number of signals as a priori information.…”

“…To this end, we proposed a novel coprime array-based algorithm that adopts the sparse recovery technique for DOA estimation under a GNSS spoofing attack. Unlike previous methods in [6,8,12], our method combines virtual array interpolation and off-grid error compensation to obtain better estimation performance, and it does not require a pre-estimation of the number of incident sources. Notably, the proposed method takes advantage of the raw digital baseband signal, hence it can identify authentic signals and spoofing before the despreading stage of the receiver, which avoids signal acquisition, tracking and the position solution.…”