Based on sparse representations, the problem of two-dimensional (2-D) direction of arrival (DOA) estimation is addressed in this paper. A novel sparse 2-D DOA estimation method, called Dimension Reduction Sparse Reconstruction (DRSR), is proposed with pairing by Spatial Spectrum Reconstruction of Sub-Dictionary (SSRSD). By utilizing the angle decoupling method, which transforms a 2-D estimation into two independent one-dimensional (1-D) estimations, the high computational complexity induced by a large 2-D redundant dictionary is greatly reduced. Furthermore, a new angle matching scheme, SSRSD, which is less sensitive to the sparse reconstruction error with higher pair-matching probability, is introduced. The proposed method can be applied to any type of orthogonal array without requirement of a large number of snapshots and a priori knowledge of the number of signals. The theoretical analyses and simulation results show that the DRSR-SSRSD method performs well for coherent signals, which performance approaches Cramer–Rao bound (CRB), even under a single snapshot and low signal-to-noise ratio (SNR) condition.

In this paper, the method of direction-of-arrival (DOA) estimation for wideband signals based on sparse representation of FRFT domain is proposed by using the excellent convergence of FRFT to LFM signals. This method focuses the wideband signal to the reference frequency using FRFT, establishes the DOA estimation model and the array manifold matrix in the FRFT domain, and reconstructs the spatial spectral function based on the sparse representation of the spatial angles, so as to realize the wideband LFM signal DOA estimations. The method not only is suitable for non-coherent signals but also can process coherent signals directly without any decoherent operations; in addition, the number of signals is not necessarily known a priori. Simulation results show that the proposed method can achieve better estimation performance and higher angular resolution, especially under low signal-to-noise ratio (SNR) condition.

Simultaneous wireless information and power transfer (SWIPT) technology provides an efficient solution to energy-limited communication terminals in a wireless network. However, in the current application scenario of SWIPT technology, relays use all the collected energy forwarding to assist communication between source nodes, while ignoring the fact that relays can accumulate and store energy. This is of great practical significance in collaborative communication. By using a transmission scheme of a time-division broadcast for the direct transmission link, improvement of the system diversity gain through combining the technology at the receiver can be realized. Based on the above, we propose a two-way relay energy accumulation communication system, which is extended from a single relay system to a multi-relay system. The instantaneous transmission rate of the system link and the system equivalent profit are optimized by jointly optimizing the relay selection, time slot allocation factor, power splitting factor and relay transmit power. Compared with the comparison algorithm, the proposed algorithm shows a significant improvement in the performance of the system.

In radar array signal processing, weak nonstationary polarization signal direction of arrival (DOA) estimation is a challenging and significant issue when both strong and weak nonstationary signals coexist. Time-frequency (T-F) analysis is an effective method to deal with nonstationary signals. In the last decade, spatial time-frequency distributions (STFDs) have been proposed for multiple dual-polarization antenna arrays and efficaciously used for nonstationary signal DOA estimation. In this article, we introduced a novelty means for estimating weak nonstationary polarization signal DOA by utilizing spatial polarimetric time-frequency distributions (SPTFDs) of cross terms when there are strong nonstationary polarization interference signals and additive Gaussian white noise. The cross terms’ SPTFDs are considered via a replaceability matrix for data covariance in multiple signal classification (MUSIC) and the estimation of signal parameters using the rotational invariance technique (ESPRIT). Combining the STFDs of cross terms with polarization information about weak nonstationary signals improves signal DOA estimation accuracy. The combined MUSIC and ESPRIT are used in the algorithm to further ensure the success probability and accuracy of DOA estimation. Through simulation analyses, the proposed algorithm is more suitable for the required application scenarios than other algorithms and is superior to other algorithms.

A spatially polarized time‐frequency distribution (SPTFD) based on dual‐polarized double‐fed antenna arrays is adapted to deal with polarization‐unstable signals. A linear time‐frequency (TF) representation was used for an instantaneous frequency (IF) estimate, primarily due to its simplicity and immunity to cross‐interference. Using a set of linear TF transformations using Gaussian windows and Fourier oscillation kernels, the IF estimated window widths of multiple unstable signals are obtained. This paper introduces a new method for estimating the direction of arrival (DOA) of polarized waves using adaptive linear time‐frequency transforms. In this paper, a narrowband far‐field point source on the receiving array is analyzed. The source signal is split into two orthogonally polarized components. The optimal window is determined by the first derivative of the IF; for this purpose, we take a simple algorithm for solving the derivative and optimize it. In developing TF‐adaptive and fully automatic TF display technology, the first method is to use the time‐adaptive window for minimizing the IF estimate mean square error (MSE) sum at each moment, while the second procedure is to adjust according to time and frequency and minimize estimate MSE sum at each position in the TF region. Due to its combination with signal polarization, the spatial time‐frequency distribution (STFD) gains more freedom and thus perfects the phonon space estimation of noise and signal. On the SPTFD platform, polarized time‐frequency multiple signal classification (PTF‐MUSIC) is used for the estimation of signal direction of arrival, which outperforms conventional time‐frequency MUSIC. Using the example of a synthesized signal, this method outperforms conventional techniques in DOA estimation.