Chunmao Yeh

Cross-Range Scaling for ISAR Based on Image Rotation Correlation

For better understanding of the imaging result provided by inverse synthetic aperture radar (ISAR), it is more desirable to present it from the conventional range-Doppler domain to the homogeneous range-cross-range domain. To accomplish the process of cross-range scaling, the rotating velocity (RV) of the target should be estimated first. For a uniformly planar rotating object, a novel method based on a concept of rotation correlation is proposed to obtain the RV in this letter, and neither prominent scattering centers nor phase coefficient extraction is required. Furthermore, a three-step fast-Fourier-transform-based convolution interpolation scheme is proposed to realize the above correlation, which makes the proposed method more efficient for implementation. Finally, experimental results with both simulated and real ISAR data are provided to demonstrate the effectiveness of the proposed method for different targets.

Multiple-GPU accelerated range-Doppler algorithm for synthetic aperture radar imaging

Parallelization based on general purpose graphic processing unit (GPGPU) is a kind of promising technology widely used to improve the computing performance. GPU is designed for data parallel and computational intensive applications. In this paper, a data processor based on multiple GPGPU devices is proposed for SAR signal processing. Some key technologies are emphasized for exploiting the best performance of GPGPU. And the processors performance is demonstrated by the implementation of range-Doppler imaging algorithm, which shows it is suitable for real-time SAR signal processing.

Modified Three-Component Decomposition Method for Polarimetric SAR Data

In this letter, a modified three-component model-based decomposition method is proposed to solve the problem of instability present in the Freeman decomposition method. We incorporate the similarity parameter and introduce a new constraint that describes the relationship between the powers of scattering components. The proposed method minimizes a continuous objective function under a set of constraints, which results in the stability of the decomposition method. Furthermore, a fast algorithm for solving the optimization problem is developed to accelerate computation. We demonstrate the stability of the proposed decomposition method by using the E-SAR polarimetric data acquired over the Oberpfaffenhofen area.

Cross-range scaling for ISAR via optical flow analysis

For high resolution imaging applications, ISAR can be viewed as a kind of camera which linearly maps the scattering centers from the physical plane to the RD image plane. Thus, the concept and methods of optical flow in computer vision may be introduced for the rotation estimation in ISAR. Furthermore, three kinds of optical flow analysis-based estimators, namely triangle-based, line-based, and image rotation correlation-based estimators, are provided to estimate the coo on the RD image series herein. Because the RD image series is a common output of conventional ISAR and only the scattering center operators are used, the proposed optical flow-based method may also be computationally efficient. Besides, with the increase of scattering centers and images, the high accuracy of cross-range scaling can also be guaranteed. Finally, experimental results are provided to demonstrate the effectiveness of proposed methods based on some measured data of Yak airplane.

Rotation Estimation for ISAR Targets With a Space–Time Analysis Technique

A new method for estimating the rotational motion of a noncooperative target is presented by exploiting the 2-D space-variant characteristic of inverse synthetic aperture radar imaging. With a space-time analysis technique, the position variation of every extracted scattering center in both the range and cross-range directions can be utilized for rotation estimation. This method differs substantially from conventional methods that exploit high-order terms of the Doppler frequency, i.e., only the position variation in the cross-range direction. An iterative processing scheme is proposed to extract as many scattering centers as possible from the phase history of returned echoes. Experimental results with some measured airplane data demonstrate the effectiveness of the proposed method.

ISAR image fusion with two separated aspect observations

Finer image resolution may be obtained with larger accumulated aspect angle for inverse synthetic aperture radar (ISAR), which may be provided by two mono-static ISAR systems. To form finer images with co-planar observations at different aspects, parameters such as the rotating of the non-cooperative moving object and the aspect angle difference between them must be provided. In this paper, a method is proposed to estimate these parameters based on sub-pixel level position extraction of prominent scattering centers on the range-Doppler images. Also, the implementation of the proposed method is introduced, and numeric experiments are provided to demonstrate the effectiveness of the proposed method.

Simultaneous range and radial velocity estimation with a single narrowband LFM pulse

The mismatch effect induced by the radial motion of a target is analyzed for linear frequency modulated (LFM) signals. Then, a novel integrated processing scheme is proposed to resolve the delay-Doppler coupling effect in LFM pulse compression. Therefore the range and radial velocity of the target can be simultaneously estimated with a narrowband LFM pulse. Finally, numerical simulation results demonstrate the effectiveness and good performance of the proposed method.

GPGPU accelerated fast convolution back-projection for radar image reconstruction

This paper describes a parallel fast convolution back-projection algorithm design for radar image reconstruction. State-of-the-art general purpose graphic processing units (GPGPU) were utilized to accelerate the processing. The implementation achieves much better performance than conventional processing systems, with a speedup of more than 890 times on NVIDIA Tesla C1060 supercomputing cards compared to an Intel P4 2.4 GHz CPU. 256×256 pixel images could be reconstructed within 6.3 s, which makes real-time imaging possible. Six platforms were tested and compared. The results show that the GPGPU super-computing system has great potential for radar image processing.

Modified doppler centroid tracking for ISAR based on image equilibrium

Phase correction is a key step of inverse synthetic aperture radar (ISAR) motion compensation, which seriously affects the ISAR focusing and imaging quality. As a typical phase correction method, Doppler centroid tracking (DCT) method has clear principle and small computation amount. However, the performance of DCT is normally unsatisfactory when the target has strong scattering centers. Based on the analysis and comparison of existing methods, the image-domain equilibrium is proposed in this paper to improve the performance of DCT method. By using the simple operators of equilibrium and feedback, the proposed method may dramatically reduce the effect of prominent scattering centers and improve the robustness and the ultimate imaging quality. Finally, the effectiveness of the proposed method is verified via the performance analysis and imaging results of real airplane target.

Clutter modeling for bistatic SAR with phased array antenna and arbitrary geometry configuration

For bi-static synthetic aperture radar (Bi-SAR) with phased array antenna and arbitrary bi-static geometry configuration, this paper proposes a clutter modeling method for clutter suppressing and ground moving target detection. Furthermore, based on the simulated space-time clutter spectrum of four typical specific geometry configurations, the detailed analysis is also given for the clutter suppressing performance with space-time adaptive processing (STAP), Finally, some important conclusions are given for Bi-SAR with different geometry configuration.