DOA estimation method for wideband signals by sparse recovery in frequency domain

The traditional super-resolution direction finding methods based on sparse recovery need to divide the estimation space into several discrete angle grids, which will bring the final result some error. To this problem, a novel method for wideband signals by sparse recovery in the frequency domain is proposed. The optimization functions are found and solved by the received data at every frequency, on this basis, the sparse support set is obtained, then the direction of arrival (DOA) is acquired by integrating the information of all frequency bins, and the initial signal can also be recovered. This method avoids the error caused by sparse recovery methods based on grid division, and the degree of freedom is also expanded by array transformation, especially it has a preferable performance under the circumstances of a small number of snapshots and a low signal to noise ratio (SNR).

Detection of Number of Wideband Signals Based on Support Vector Machine

In array signal processing,number of signals is often a premise of estimating other parameters.For the sake of determining signal number in the condition of strong additive noise or a little sample data,an algorithm for detecting number of wideband signals is provided.First,technique of focusing is used for transforming signals into a same focusing subspace.Then the support vector machine(SVM)can be deduced by the information of eigenvalues and corresponding eigenvectors.At last,the signal number can be determined with the obtained decision function.Several simulations have been carried on verifying the proposed algorithm.

DOA estimation method for wideband signals by block sparse reconstruction

For the direction of arrival（DOA） estimation,traditional sparse reconstruction methods for wideband signals usually need many iteration times.For this problem,a new method for two-dimensional wideband signals based on block sparse reconstruction is proposed.First,a prolate spheroidal wave function（PSWF） is used to fit the wideband signals,then the block sparse reconstruction technology is employed for DOA estimation.The proposed method uses orthogonalization to choose the matching atoms,ensuring that the residual components correspond to the minimum absolute value.Meanwhile,the vectors obtained by iteration are back-disposed according to the corresponding atomic matching rules,so the extra atoms are abandoned in the course of iteration,and the residual components of current iteration are reduced.Thus the original sparse signals are reconstructed.The proposed method reduces iteration times comparing with the traditional reconstruction methods,and the estimation precision is better than the classical two-sided correlation transformation（TCT）algorithm when the snapshot is small or the signal-to-noise ratio（SNR） is low.

New direction of arrival estimation method for wideband coherent signals

To estimate the direction-of-arrival （DOA） of wideband coherent signals, a new method by modifying the orthogonality of the projected suhspaces method is proposed. And it can deal with randomly position perturbed arrays by using the Toeplitz method. This method needn＇t the primary information of DOA for focusing matrix and the sector dividing of interpolated method, which improving the precision of estimation and reducing the computational complexity. Simulations illustrate the effectiveness of this method.

Wideband angle of arrival estimation of chirp signals using virtual Wignerville distribution

To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution （RWVD） of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio （SNR） condition, the proposed method exhibits better precision than the method of frequency focusing （FF）. The proposed method can be further applied to nonuniform linear array （NLA） since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.

Dual-assisted high-precision tracking technique for wideband multiplexed signals in new generation GNSS

With the evolution of Global Navigation Satellite System(GNSS),new generation GNSS signals have adopted the dual-frequency multiplexing modulation techniques,which jointly modulate multiple signals located on multiple sub-frequencies into a Wideband Multiplexed Signal(WMS).Although WMSs were proposed initially to reduce the complexity of satellite transmitters and improve the transmission efficiency of signals,their multi-component structures and wide root mean square bandwidths introduced by high-frequency subcarriers also provide the possibility to improve the GNSS ranging precision.Therefore,this paper proposes a Dual-assisted Multi-component Tracking(DMT)technique,which can not only fully use high-frequency subcarriers in WMSs,but also effectively track carrier,subcarrier,and code by jointly utilizing all components in WMS.In this paper,the tracking and ranging performances of DMT are comprehensively analyzed theoretically and by simulation and real experiments.The results show that compared with existing WMS tracking methods,DMT can achieve tracking results with lower tracking jitters and ranging results with higher precision,providing a highly advantageous solution for new generation GNSS signal processing.

FREQUENCY ESTIMATION OF SINUSIODE FROM WIDEBAND USING SUB-NYQUIST SAMPLING

A novel frequency estimation algorithm for wideband signal with sub-Nyquist sampling is proposed in this paper. With the aid of information provided by the auxiliary delayed sampling channel and the aliased frequency estimation for wideband signal with sub-Nyquist sampling, the frequency aliasing due to sub-Nyquist sampling can be solved. This method can reduce the complexity of the overall hardware at the cost of an auxiliary sampling channel. Furthermore, in order to alleviate the computation burden for its practicability, a more simplified algorithm is put forward and its validity is proved by our numerical simulation results. The Cramer-Rao Lower Bound (CRLB) of the frequency estimation is also derived at the end of this paper.

Wideband signal detection based on high-speed photonic analog-to-digital converter

This Letter demonstrates the effectiveness of a high-speed high-resolution photonic analog-to-digital converter （PADC） for wideband signal detection. The PADC system is seeded by a high-speed actively mode locked laser, and the sampling rate is multiplied via a time-wavelength interleaving scheme. According to the laboratory test, an X-band linear frequency modulation signal is detected and digitized by the PADC system. The channel mismatch effect in wideband signal detection is compensated via an algorithm based on a short-time Fourier transform. Consequently, the signal-to-distortion ratio （SDR） of the wideband signal detection is enhanced to the comparable SDR of the single-tone signal detection.