Yi Su

High-Resolution Imaging Using a Wideband MIMO Radar System With Two Distributed Arrays

Imaging a fast maneuvering target has been an active research area in past decades. Usually, an array antenna with multiple elements is implemented to avoid the motion compensations involved in the inverse synthetic aperture radar (ISAR) imaging. Nevertheless, there is a price dilemma due to the high level of hardware complexity compared to complex algorithm implemented in the ISAR imaging system with only one antenna. In this paper, a wideband multiple-input multiple-output (MIMO) radar system with two distributed arrays is proposed to reduce the hardware complexity of the system. Furthermore, the system model, the equivalent array production method and the imaging procedure are presented. As compared with the classical real aperture radar (RAR) imaging system, there is a very important contribution in our method that the lower hardware complexity can be involved in the imaging system since many additive virtual array elements can be obtained. Numerical simulations are provided for testing our system and imaging method.

Two-Dimensional Imaging via a Narrowband MIMO Radar System With Two Perpendicular Linear Arrays

This paper presents a system model and method for the 2-D imaging application via a narrowband multiple-input multiple-output (MIMO) radar system with two perpendicular linear arrays. Furthermore, the imaging formulation for our method is developed through a Fourier integral processing, and the parameters of antenna array including the cross-range resolution, required size, and sampling interval are also examined. Different from the spatial sequential procedure sampling the scattered echoes during multiple snapshot illuminations in inverse synthetic aperture radar (ISAR) imaging, the proposed method utilizes a spatial parallel procedure to sample the scattered echoes during a single snapshot illumination. Consequently, the complex motion compensation in ISAR imaging can be avoided. Moreover, in our array configuration, multiple narrowband spectrum-shared waveforms coded with orthogonal polyphase sequences are employed. The mainlobes of the compressed echoes from the different filter band could be located in the same range bin, and thus, the range alignment in classical ISAR imaging is not necessary. Numerical simulations based on synthetic data are provided for testing our proposed method.

Convex active contour model for target detection in synthetic aperture radar images

Abstract. The active contour model (ACM) is one of the most successful methods for target detection in optical and medical images, but multiplicative speckle noise greatly interferes with its use in synthetic aperture radar (SAR) images. To overcome this difficulty, a convex ACM is proposed. First, a ratio distance is defined in terms of the probability density functions on both sides of the contour. This ratio is then introduced into the Chan and Vese (CV) model. Second, by combining the modified CV and region-scalable fitting models, the global intensity fitting and local intensity fitting forces both evolve the contour. Third, the energy of the combination model is then incorporated into Chan’s global minimization active contour framework so that the global minimum can be reached. Furthermore, the gradient term in the final energy function allows the proposed model to locate boundaries more quickly and accurately. Numerically, a dual formulation is utilized to solve the problem of active contour propagation toward target boundaries. Target detection experiments in real and simulated SAR images show that the proposed model outperforms classical region-based and hybrid ACMs in terms of efficiency and accuracy.

Narrowband MIMO radar imaging with two orthogonal linear T/R arrays

Based on the spatial convolution principle of multi-input multi-output (MIMO) radar, the distribution of two orthogonal linear transmit/receive (T/R) arrays is designed. With this array structure, a two-dimensional (2-D) imaging method for narrowband MIMO radar is proposed. The simulation shows that this array can provide about the same imaging resolution but uses fewer antennas compared with a planar receive-only array.

Automatic target recognition scheme for a high-resolution and large-scale synthetic aperture radar image

Abstract. Existing automatic target recognition of synthetic aperture radar (SAR ATR) schemes mainly focus on target chips, but there is very little research for a large-scale and high-resolution SAR image that is more practical for SAR image interpretation. How to recognize targets efficiently and accurately from a large-scale and high-resolution SAR image is still a challenge. We present a scheme based on the combination of a salient detection approach, an active contour model (ACM), an affine-invariant shape descriptor, and the corresponding shape context. During the detection stage, the spectral residual approach is utilized to efficiently preselect salient regions. The proposed convex ACM, based on a ratio distance and distribution metric which makes it more robust to multiplicative speckled noise, is then adopted to get accurate candidate target chips. For the discrimination stage, a cumulative sum of multiscale lacunarity feature is proposed to select vehicle chips from clutter chips. Finally, affine-invariant shape features, obtained from the contours by our proposed ACM, are combined with a corresponding shape context to make the classification more accurate. Experimental results demonstrate that our SAR ATR system, integrating all the proposed methods, is feasible in ATR from a high-resolution and large-scale SAR image.

High-resolution imaging using a wideband MIMO radar system

In this paper we propose an imaging method via wideband multiple-input multiple-output radar to reduce the hardware complexity of the system. Since a spatial parallel procedure to sample the scattered echoes during a single snapshot illumination, instead of the spatial sequential sampling procedure during multiple snapshot illuminations in classical ISAR imaging, is utilized in our method, the complex motion compensation in ISAR imaging can be avoided. Moreover, compared to the narrowband MIMO imaging system, every array element transmits and receives simultaneously in our array configuration, and therefore, the hardware complexity can be significantly reduced. Numerical simulations are provided for testing our proposed method.

High-resolution imaging using a narrowband MIMO radar system

This paper presents a system model and method for the two-dimensional (2-D) imaging application via a narrowband multiple-input multiple-output (MIMO) radar system with two perpendicular linear arrays. The proposed method utilities the spatial parallel procedure sampling the scattered echoes during a single snapshot illumination, instead of the spatial sequential one sampling the scattered echoes during multiple snapshot illuminations in inverse synthetic aperture radar (ISAR) imaging. Consequently, the complex motion compensation in ISAR imaging can be avoided. Furthermore, in our array configuration, multiple narrowband shared-spectrum waveforms coded with orthogonal polyphase sequences are employed to illuminate a target. The mainlobe of the compressed echoes from the different filter band for all scatterers could be located in the same range bin, and thus, complex range alignment in classical ISAR imaging is not necessary. Numerical simulations based on synthetic data are provided for testing our proposed method.

A new parameter estimation for K distribution clutter

K distribution is one of the most widely applied statistical models for SAR images clutter. Now there are several approaches to estimate the parameters of K distribution. Based on Raghavanpsilas method, a new method named piecewise-approximation is given in this paper, where gamma and beta-prime distributions are applied to piecewisely approximate K distribution. The experiment results show that the new method broadens the applicable range of parameter, and has a higher accuracy than the method of moment.

A novel scheme of unsupervised target detection for high-resolution SAR image

How to detect the interested targets efficiently and accurately from a large-scale and high-resolution synthetic aperture radar (SAR) image is still a research challenge. This paper presents a novel scheme based on saliency detection approach and active contour model (ACM) for SAR image detection. Due to the high efficiency of Spectral Residual (SR) approach, the scheme can find the potential interested regions rapidly. Then a modified local and global intensity fitting (MLGIF) ACM based on ratio and distribution metric is proposed in this paper, which overcomes the defect of some well-known ACMs tending to fall into local minimums in SAR image detection. Due to the robustness of the MLGIF model to multiplicative speckle, the detection scheme can locate the targets more accurately and is more suitable to SAR image processing. Experiments of large-scale and high resolution SAR image detection show that the proposed scheme outperforms classical Constant False Alarm Rate (CFAR) Detector in terms of the efficiency and false alarm.