Dazhuan Xu

NOVEL BLIND JOINT DIRECTION OF ARRIVAL AND POLARIZATION ESTIMATION FOR POLARIZATION-SENSITIVE UNIFORM CIRCULAR ARRAY

A novel blind Direction of arrival (DOA) and polarization estimation method for polarization-sensitive uniform circular array is investigated in this paper. An analysis of the received signal of the polarization-sensitive uniform circular array shows that the received signal has trilinear model characteristics, and hence trilinear decomposition-based blind DOA and polarization estimation for polarization sensitive uniform circular array is proposed in this paper. Our proposed algorithm has better DOA and polarization estimation performance. Our proposed algorithm can be thought of as a generalization of ESPRIT, and has wider application than ESPRIT method. The useful behavior of the proposed algorithm is verified by simulations.

On the MUSIC-derived Approaches of Angle Estimation for Bistatic MIMO Radar

We investigate the topic for the direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic multiple-input-multiple-output (MIMO) radar systems with the exploitation of array invariance. Several MUSIC-derived algorithms for angle estimation in MIMO radar have been presented and compared for their complexity costs against that of ESPRIT. The proposed scheme of multi-invariance multiple signal classification (MI-MUSIC) has the best performance and also can be considered as a generalization of MUSIC. Simulations verify the collaborative usefulness of our algorithm.

Blind PARAFAC signal detection for polarization sensitive array

This paper links the polarization-sensitive-array signal detection problem to the parallel factor (PARAFAC) model, which is an analysis tool rooted in psychometrics and chemometrics. Exploiting this link, it derives a deterministic PARAFAC signal detection algorithm. The proposed PARAFAC signal detection algorithm fully utilizes the polarization, spatial and temporal diversities, and supports small sample sizes. The PARAFAC algorithm does not require direction-of-arrival (DOA) information and polarization information, so it has blind and robust characteristics. The simulation results reveal that the performance of blind PARAFAC signal detection algorithm for polarization sensitive array is close to nonblind MMSE method, and this algorithm works well in array error condition.

Blind DOA and polarization estimation for polarization-sensitive array using dimension reduction MUSIC

A novel blind direction-of-arrival (DOA) and polarization estimation algorithm for polarization-sensitive uniform linear array using dimension reduction multiple signal classification (MUSIC) is proposed in this paper. The proposed algorithm utilizes the signal subspace to obtain an initial estimation of DOA, then estimates more accurate DOA through a one-dimensional (1-D) local searching according to the initial estimation of DOA, and finally obtains polarization parameter estimation via the estimated polarization steering vectors. The proposed algorithm, which only requires a one-dimension local searching, can avoid the high computational cost within multi-dimensional MUSIC algorithm. The simulation results reveal that the proposed algorithm has better DOA and polarization estimation performance than both estimation of signal parameters via rotational invariance technique algorithm and trilinear decomposition algorithm. Furthermore, the proposed algorithm can be suitable for irregular array geometry, obtain automatically paired multi-dimensional parameter estimation, and avoid multi-dimensional searching. Simulation results verify the effectiveness of the proposed algorithm.

Novel blind carrier frequency offset estimation for OFDM system with multiple antennas

In this paper, we address the problem of carrier frequency offset (CFO) estimation for Orthogonal Frequency Division Multiplexing (OFDM) systems with multiple antennas. The received signal can be denoted as a trilinear model, then the trilinear decomposition-based CFO estimation algorithm is proposed. Comparing to both ESPRIT method and the cyclostationarity (CS) approach, the algorithm that we presented has improved CFO estimation performance. Furthermore, our proposed algorithm can even work in condition of no virtual carrier. Simulation results illustrate performance of this algorithm.

Improved coherent DOA estimation algorithm for uniform linear arrays

An improved algorithm on coherent direction-of-arrival (DOA) estimation is presented in this article, with the objective to overcome the unsatisfactory performances of estimation of signal parameter via rotational invariance techniques (ESPRIT)-like algorithms (Han and Zhang, IEEE Antennas and Wireless Propagation Letters 2005;4:443–446). On the basis of trilinear model by reconstructing a series of Toeplitz matrix from the co-variance matrix of array output, our proposed algorithm is to resolve the DOAs of coherent signals, which not only has much better DOA estimation performance than algorithms of ESPRIT-like and multi-invariance ESPRIT but also identifies more DOAs than ESPRIT-like algorithm. Simulation results demonstrate its validity.

Multi-Invariance ESPRIT-Based Blind DOA Estimation for MC-CDMA With an Antenna Array

In this paper, we address the problem of direction-of-arrival (DOA) estimation for a multicarrier code-division multiple-access (MC-CDMA) system with an antenna array. We reconstruct the received signal to form a data model with a multi-invariance property, and then, a multi-invariance estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm for DOA estimation is proposed. This algorithm has improved DOA estimation performance and identified more DOAs compared with an ESPRIT algorithm. Moreover, our algorithm enables DOA estimation of a large number of impinging waves. Simulation results illustrate the performance of this algorithm.

NOVEL BLIND JOINT DIRECTION OF ARRIVAL AND FREQUENCY ESTIMATION FOR UNIFORM LINEAR ARRAY

This paper links joint direction of arrival (DOA) and frequency estimation problem to the trilinear model and derives a novel blind joint angle and frequency estimation algorithm. The proposed algorithm has better performance than ESPRIT algorithm. Our proposed algorithm is thought of as a generalization of ESPRIT. The useful behavior of the proposed algorithm is verified by simulations.

Performance of belief propagation coded modulation with iterative decoding

We consider bit-interleaved coded modulation with iterative decoding for bandwidth-efficient transmission over Rayleigh fading channel. A serially concatenated iterative scheme (BPCM-ID) combining low-density parity-check codes (LDPC) with multilevel modulation is proposed. Differing from other serially concatenated iterative decoding schemes, the whole iterative process of BPCM-ID is divided into outer iteration and inner iteration to avoid too much error feedback to the demapper which may cause severe degradation of decoding performance. It helps to improve the robustness of the system. Another advantage, in contrast to using convolutional codes or turbo codes, is its low complexity while maintaining high BER performance because the check equations are used to terminate the both iterations. We also study the different mapping constellations for 16-QAM. Simulations show that BPCM-ID can achieve not only large coded gains but also diversity with robust convergence performance and low complexity.

Blind Joint DOA and Dod Estimation and Identifiability Results for MIMO Radar with Different Transmit / Receive Array Manifolds

This paper derives its link of direction of arrival (DOA) and direction of departure (DOD) estimation problem for multi- input multi-output (MIMO) radar to the trilinear model. With the exploitation of this link, we present a trilinear decomposition- based blind algorithm for angle estimation in MIMO radar. After the algorithmic presentation and discussions for identiflability results, trilinear decomposition-based angle estimation under difierent array conditions has also been investigated. Our proposed algorithm works well without either spectral peak searching or pair matching, has better angle estimation performance than ESPRIT, and even supports small sampling sizes. Simulation trials testify that the merits of our algorithmic performance are in collaboration with theoretical flndings.