Minglei Yang

Thermos Array: Two-Dimensional Sparse Array with Reduced Mutual Coupling

Sparse planar arrays, such as the billboard array, the open box array, and the two-dimensional nested array, have drawn lots of interest owing to their ability of two-dimensional angle estimation. Unfortunately, these arrays often suffer from mutual-coupling problems due to the large number of sensor pairs with small spacing d (usually equal to a half wavelength), which will degrade the performance of direction of arrival (DOA) estimation. Recently, the two-dimensional half-open box array and the hourglass array are proposed to reduce the mutual coupling. But both of them still have many sensor pairs with small spacing d, which implies that the reduction of mutual coupling is still limited. In this paper, we propose a new sparse planar array which has fewer number of sensor pairs with small spacing d. It is named as the thermos array because its shape seems like a thermos. Although the resulting difference coarray (DCA) of the thermos array is not hole-free, a large filled rectangular part in the DCA can be facilitated to perform spatial-smoothing-based DOA estimation. Moreover, it enjoys closed-form expressions for the sensor locations and the number of available degrees of freedom. Simulations show that the thermos array can achieve better DOA estimation performance than the hourglass array in the presence of mutual coupling, which indicates that our thermos array is more robust to the mutual-coupling array.

A New Nested MIMO Array With Increased Degrees of Freedom and Hole-Free Difference Coarray

We propose a new antenna array design approach for a multiple-input and multiple-output (MIMO) radar, which has closed-form expressions for the sensor locations and the number of achievable degrees of freedom (DOFs). This new approach utilizes the nested array as transmitting and receiving arrays. We employ the difference coarray of the sum coarray (DCSC) of the MIMO radar to obtain more DOFs for direction-of-arrival (DOA) estimation. Via properly designing the interelement spacings of the transmitting and receiving arrays, we can obtain a hole-free DCSC. The characteristics of array geometries are analyzed and the optimal numbers of sensors in transmitting/receiving antenna array are derived when given the total number of physical sensors. Simulations are conducted to demonstrate the advantages of the proposed array in terms of the number of DOFs, the number of resolvable sources, and the DOA estimation performance over the coprime MIMO array.

Transmitter polarization optimization with polarimetric MIMO radar for mainlobe interference suppression

Polarization diverse design of the transmit waveforms based on the property of the target scattering matrix provides better performance than transmitting waveforms with fixed polarizations, especially for mainlobe interference suppression applications. In this work, we propose a radar system combines the advantages of multiple-inputmultiple-output (MIMO) systems with the advantages offered by optimally choosing the transmitter polarizations, in order to achieve a better mainlobe interference suppression performance. The polarization diversity is employed in the transmit array, while the receive array adopts 2-D vector sensors to measure the horizontal and vertical components of the received signal. The optimal transmitter polarizations can be obtained by maximizing the output signal-to-interference-plus-noise ratio (SINR) in each coherent processing interval (CPI). In addition, the discrimination method for the target and the interference is studied in this paper, along with the target scattering matrix estimation method. Simulation results demonstrate that interference can be effectively discriminated and suppressed with the radar configuration, and better interference suppression performance is achieved with the optimal transmitter polarizations.

Low angle direction of arrival estimation by time reversal

In a low angle target parameter estimation scenario, the backscattered signals from targets are distorted by clutter and multipath, which degrades the performance of direction-of-arrival (DOA) estimator significantly. This paper presents a novel method using time reversal (TR) technique and coherent signal-subspace method (CSM) for DOA estimation in a low angle scenario. The TR method exploits target information contained in the return echoes due to multipath and adaptively adjusts TR probing waveforms to increase the signal-to-noise ratio (SNR). Furthermore, CSM is adopted to focus the energy of the multipath signal in a predefined subspace so as to exploit the full time-bandwidth product of the target source. We analyze the performance of the proposed new DOA algorithm. Numerical simulations demonstrate its superior performance compared with the conventional DOA estimators.

Altitude Measurement of Low-elevation target for VHF Radar Based on Weighted Sparse Bayesian Learning

In this study, a novel method is proposed to deal with the problem of altitude measurement of a low-elevation target for very high frequency radars in complex terrains. The problem typically concerns about the direction-of-arrival (DOA) estimation method for closely spaced and correlated signals arose by multipath propagation, in which the multipath signal would be modulated by the rough and irregular reflecting surface, result in amplitude and phase perturbation and energy fluctuations of the receiving signals. A perturbation multipath propagation model is derived where the influence of irregular reflecting in complex terrain is taken as a random perturbation of the multipath signal. The spatial sparsity of the receiving signal is then exploited, and a weighted sparse Bayesian learning method is proposed to estimate both the random perturbation coefficients and DOA of the incident signal with high precision. Both the computer simulations and real data analysis indicate the efficiency and superior performance of the proposed method in dealing with altitude measurement in complex terrain.

Design and implementation of a T/R module automatic test system

Transmit/Receive (T/R) module is a key part of Active phased array radar (APAR). It is necessary to test (T/R) the module strictly before it is set up into the radar system, which is called Off-Line Test. An APAR system is generally composed of thousands of T/R modules, which results in the heavy test task. For the difficulties of heavy test task and complex operations, a T/R module automatic test system is introduced in this paper, including the design of the hardware platform and software system, especially the data processing and the timing control design. The system is applied successfully at present and shortens the test time to 0.5 hour from the traditional 20 hours for a Ku-band T/R module with 16 channels. It is characterized by high test efficiency, accurate measurement results and easy operation, hence solving the difficulties of T/R module test effectively.

Experimental system and results for distributed VHF radar

To solve the shortcomings of the Very High Frequency (VHF) radar, such as wide beam-width, low angular resolution and weak transportability, we propose a novel distributed VHF radar which consists of two identical VHF digital array radars. The system scheme of the experimental system and the main functions of the subsystems are given in this paper. We also design the signal processing method for the real data of the distributed VHF radar. The results of the real data show that the beam width of the distributed array is much narrower than that of the sub-arrays. And the accuracy of the angle estimation is around 1/10 that of the sub-arrays. Therefore, the proposed system can reach a high angle estimation accuracy with a relatively low cost and high transportability.

The applications and future of synthetic impulse and aperture radar

The Synthetic Impulse and Aperture Radar (SIAR), which is a typical Multiple Input Multiple Output (MIMO) radar with orthogonal frequency waveforms, has the advantages of more degrees of freedom, higher angular resolution and target detection probability than traditional phased array radar. In this paper, a brief introduction of the basic features and the advantages of SIAR is given first. Then two applications used in high frequency surface wave and microwave band are presented with some real data results. Finally, we discuss the possible applications and its future.

Target discrimination method with polarimetric radar

Polarization diverse design of the transmit waveforms based on the property of the target scattering matrix provides better performance than transmitting waveforms with fixed polarizations. In this work, we study the target discrimination method under the active-decoys scenario with the polarimetric radar. The polarization diversity is employed in transmit antennas. We transform the target discrimination problem into a binary hypothesis problem. In the meanwhile, we study the vector discrimination model and scalar discrimination model. Otherwise, the discrimination probabilities for the true target and the false target are derived. Using numerical simulations, we demonstrate that optimal design of the transmitter polarizations provides improved discrimination performance over the radar with only horizontally and vertically polarized transmit antennas.

A novel off-grid DOA estimation via weighted subspace fitting

In this paper, a novel off-grid direction-of-arrival (DOA) estimation algorithm involving sparse recovery is proposed based on weighted subspace fitting, in which multiple snapshots are used and effects of off-grid DOA are taken into account. The DOA estimation problem is formulated as a binary cost function, then an iterative sparse recovery algorithm alternating resolved the unknown variables with weighted linorm approximation method is developed to estimate DOA accurately. The proposed algorithm obtains improved accuracy compared with the existing methods. Simulation results demonstrate that the proposed algorithm can estimate the DOA with high accuracy for correlated signals while maintaining a relatively low computational cost.