ISAR imaging of uniformly rotating targets via parametric matching pursuit

Abstract

Inverse synthetic aperture radar (ISAR) imaging of maneuvering targets via matching pursuit (MP) can produce high resolution and remove sidelobe effect, providing that the target rotation rate is already known. For non-cooperative uniformly rotating targets, the rotation rate is unknown and should be retrieved together with the ISAR image. In this paper, a computational efficient parametric MP is proposed to simultaneously retrieve the rotation rate and the high-resolution ISAR image. The joint estimation of ISAR image and rotation rate is converted into alternate independent estimations, i.e. alternately estimating the ISAR image and rotation rate in an iterative manner. With the iterations, the rotation rate estimate converges to the true value and meanwhile the clear ISAR image with high resolution and low sidelobes may be obtained. Numerical examples show that the approach is efficient in estimating the real target rotation rate and recovering the high resolution ISAR image.

Comparison of parametric sparse recovery methods for ISAR image formation

“…Instead of the one-dimensional search method provided in the last subsection, a more computational efficient adaptive sparse recovery strategy has been introduced in [20]. The joint estimation of the ISAR image and unknown rotation rate can be solved by alternately estimating the ISAR image and rotation rate in an iterative manner.…”

“…Since the methods in [18,19] must repeat the image formation procedure via sparse recovery for a number of candidate rotation rates, we proposed an adaptive sparse recovery algorithm in [20], where the sparse representation can be adaptively refined to match the received radar echo. The joint estimation is solved by alternately estimating the ISAR image and rotation rate in an iterative manner.…”

“…parametric weighted L 1 minimization, is proposed in [21] to further improve the ISAR image quality. In this paper, we fully compare above parametric sparse recovery algorithms [18][19][20][21] on three aspects: the accuracy of the rotation rate estimation, the ISAR image quality and the computational load.…”

Stealth Performance Measurement for Radar Targets Based on Railborne Pseudo-Turntable Imaging

“…Some special targets are required to have the stealth ability against radars in the procedure of design, such as military aircrafts and missiles; it is generally desired to obtain small RCS in some polarization mode when they are flying towards radars [1]. RCS reduction techniques mainly include material selection and shape designs [2,3,6].…”

“…Just like that signal spectrum can not express the time-varying characteristics of frequency; overall RCS can not characterize spacevarying characteristics of echo power, so that it is not clear which parts or components of the targets have maximum contributions to the echo power at an assigned perspective according to overall RCS. Hence, we are unable to take measurements to reduce the RCS efficiently [1][2][3]. An ingenious method is proposed here, i.e., not only measuring the overall RCS of all aspects, but also measuring high resolution two-dimensional projection of extended targets at all perspectives in the radar imaging plane.…”