Search

High-resolution inverse synthetic aperture radar (ISAR) imaging and recognition of ship target is very important for many applications. Although the principle of ISAR imaging of ship target on the sea is the same as that of flying target in the sky, the former usually has more complex motion (fluctuation with the oceanic waves) than the latter, which makes the motion compensation very difficult. However, the change in phase chirp rate caused by the complex motion of ships will deteriorate the azimuth focusing quality. In this paper, we first model the complex motion of ship target with cubic phase terms (parameterised on chirp rate and its change rate), then a new ISAR imaging method, referred to as TC-DechirpClean, is proposed, which estimates the chirp rate and the change rate of chirp rate of all scatters in the time–chirp distribution plane. Both numerical and experimental results are provided to demonstrate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

Rihaczek and Hershkowitz have proposed that radar scattering from man-made targets is dominated by cavity-type reflectors that do not meet the assumptions of point scatterer theory. The effect of such dispersive scattering is to produce spurious bright responses in the radar image that can appear as a number of peaks lying along an arc. If such arc-type responses do exist in radar imagery then their removal would enhance the ability to focus moving target imagery and to perform automatic target recognition. Rihaczek and Hershkowitz have outlined a method for identifying such arc-type responses that use the image phase. Algorithms have been written to automate the outlined procedure and used to analyse a large number of synthetic and inverse synthetic aperture radar images. Arcs are present in most radar images of static and moving ground targets. To investigate whether the arcs are due to a physical mechanism or a chance occurrence, randomised target imagery was generated and also analysed. No significant differences are seen between the distributions of arc numbers obtained from randomised and real imagery. In conclusion, the arcs present in the real imagery are likely to occur by chance, rather than because of an underlying scattering mechanism. [ABSTRACT FROM AUTHOR]

Inverse synthetic aperture radar (ISAR) imaging is a powerful tool for the characterization of scattering properties of radar targets. In particular, near-field techniques allow for short distance imaging with results comparable to those of standard far-field ISAR techniques. The resulting near-field images can be used to extract the far-field radar cross section (RCS) of the target overcoming the need for long-range measurement setups. This paper compares different near-field imaging techniques and reveals an in-depth insight into the imaging process, especially with regard to the subsequent RCS extraction. The performance of the different techniques together with processing improvements are demonstrated by means of numerical target models as well as by measured data of test objects and a scaled aircraft model. [ABSTRACT FROM AUTHOR]

We present an evaluation of the impact of a recently proposed synthetic aperture radar (SAR) imaging technique on feature enhancement and automatic target recognition (ATR) performance. This image formation technique is based on nonquadratic optimization, and the images it produces appear to exhibit enhanced features. We quantify such feature enhancement through a number of criteria. The findings of our analysis indicate that the new feature-enhanced SAR image formation method provides images with higher resolution of scatterers, and better separability of different regions as compared with conventional SAR images. We also provide an ATR-based evaluation. We run recognition experiments using conventional and feature-enhanced SAR images of military targets, with three different classifiers. The first classifier is template based. The second classifier makes a decision through a likelihood test, based on Gaussian models for reflectivities. The third classifier is based on extracted locations of the dominant target scatterers. The experimental results demonstrate that the new feature-Enhanced SAR imaging method can improve the recognition performance, especially in scenarios involving reduced data quality or quantity. [ABSTRACT FROM AUTHOR]

Proposes extending the target feature extraction capacities of the CLEAN/RELAX algorithm for radar images. Application of generalized wavelets; variability of the signatures.

MIT Lincoln Laboratory is investigating the detection and identification of stationary ground targets in high resolution, fully polarimetric, synthetic aperture radar (SAR) imagery. This article (1) provides a brief description of the Lincoln Laboratory SAR, (2) describes an optimum polarimetric processing technique used to construct minimum-speckle SAR intensity imagery, and (3) presents examples of polarimetrically processed imagery. [ABSTRACT FROM AUTHOR]