Cross-range Scaling Research Articles

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.

Pitch estimation for non-cooperative maritime targets in ISAR scenarios

Maritime targets are usually involved in complex motions that complicate the generation of focused inverse synthetic aperture radar (ISAR) images and their scaling in cross-range. By assuming some hypotheses that translate to some restrictions in the maritime surveillance scenario, a signal model for the phase history is derived. This function is calculated here using phase gradient autofocus and can be related to the pitch motion of the ship, which may consequently be estimated. The amplitude and the period of this pitch estimate allow us to select imaging times at which the ISAR images are descriptive for classification purposes. The cross-range scaling of these images is also achieved. Simulated data are used to validate the technique and to evaluate its performance when deviations from the nominal scenario are present. Results obtained with live data acquired by a high-resolution radar confirm the effectiveness of the approach.

Image-based scaling for ship top view ISAR images

A high quality top view or side view ship ISAR image with proper cross-range scale is very useful for target recognition. A technique aiming at solving the ship top view image scaling is developed, in which the cross-range scale information is obtained by measuring the slopes of the two feature lines of the ship, the centerline and the stern line. Neither the prior knowledge about the ship nor the tracking data is required. The proposed technique is fully based on the image. It is used with ease and high efficiency. Examples are provided to demonstrate its effectiveness with both simulated and real data. The scaled results are in accordance with the real shape of the ship.

Novel approach for ISAR image cross-range scaling

Inverse synthetic aperture radar (ISAR) imaging systems produce electromagnetic images of targets in the range-Doppler domain. In order to rescale the image in a homogeneous range-cross range domain (meters by meters), the modulus of the target effective rotation vector must be known. Although in some cases it can be retrieved by means of ancillary data, in most cases the modulus of the target effective rotation vector must be estimated. A blind technique is proposed for estimating the modulus of the target effective rotation vector that exploits information carried by the chirp rate of scattering centres. A technique based on image segmentation, local polynomial Fourier transform (LPFT), and image contrast (IC) maximisation is used in order to extract the scattering centres and estimate their chirp rate. Simulated and real data analyses are provided to confirm the effectiveness of the proposed algorithm.

Automatic recognition of ISAR ship images

Inverse synthetic aperture radar (ISAR) produces images of ships at sea which human operators can be trained to recognize. Because ISAR uses the ship's own varying angular motions (roll, pitch, and yaw) for cross-range resolution, the viewing aspect and cross-range scale factor are continually changing on time scales of a few seconds. This and other characteristics of ISAR imaging make the problem of automatic recognition of ISAR images quite distinct from the recognition of optical images. The nature of ISAR imaging of ships, and single-frame and multiple-frame techniques for segmentation, feature extraction, and classification are described. Results are shown which illustrate a capability for automatic recognition of ISAR ship imagery.