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Direction-of-arrival (DOA) estimation methods have become increasingly significant factors in the study of communication involving radar, sonar, and wireless technology (Dong et al., 2022; Mei et al., 2021). DOA estimation technology determines the direction of signal sources, providing essential information for tasks like signal separation, positioning, and tracking (Wang et al., 2023). The concept of coprime arrays and non-circular signals has garnered significant attention in the signal processing community. Non-circular signals possess unique statistical characteristics that can enhance DOA estimation accuracy (Zhang et al., 2021; Teng et al., 2021). Developing a fast DOA estimation method for improper Gaussian signaling (IGS) non-circular signals using coprime arrays is, therefore, both an innovative and practical task.
A coprime array is a sparse array composed of two or more subarrays with coprime periods. With an appropriate array configuration, coprime arrays can reduce the number of array elements and system complexity while maintaining high resolution. The coprime array is also able to use sparse characteristics to improve the robustness. In wireless communication, many signals have non-circular characteristics, such as modulated and multipath signals (Qin et al., 2023). Non-circular signals not only contain amplitude and phase information, but they also possess special statistical properties, such as the conjugate symmetry of signals (Jian et al., 2022; Sharifzadel Lari, & Abbasi-Moghadam, 2022). These characteristics enable non-circular signals to provide more effective information regarding DOA estimation and improve both estimation accuracy and performance.
DOA estimation technology has a wide range of application value across many fields. In radar communication, DOA estimation can achieve target positioning and tracking, as well as providing key information for military reconnaissance and missile defense (Baidoo et al., 2023). In the field of wireless communication, DOA estimation can be used for signal separation and multi-user detection to improve the performance and capacity of communication systems. In addition, DOA estimation can be applied to research areas such as sonar, speech recognition, and earthquake monitoring strategies, providing crucial technical support for advancements in these areas (Gupta & Agrawal, 2021; Yuan et al., 2023).
This study proposes a fast DOA estimation method for IGS non-circular signals based on coprime array—a method that combines the advantages of coprime arrays and non-circular signals, achieving both high accuracy and low computational complexity in DOA estimation. Specifically, an IGS non-circular signal model was constructed, based on coprime array; the researchers then designed an ANCM algorithm for fast DOA estimation. This algorithm uses the non-circular characteristics of the signal, in that the pseudo-covariance matrix of the non-circular signal is not zero; this improves DOA estimation performance. By constructing a real-valued extended array output matrix, and an extended covariance matrix, the extended propagator method was used to replace the eigen-decomposition of the extended covariance matrix. This model successfully obtained the noise subspace, meaning that the DOA estimation of the target could be achieved by using the polynomial rooting method.