A general synthetic aperture radar (SAR) signal model is derived based on the Maxwells equation, and three
numerical simulations are analyzed and discussed. With this signal model, compressive sensing is applied to get
a better image.
In this paper, a denoise approach is proposed to reduce the speckle noise in SAR images
based on compress sensing. Through the skill of compressed sensing, we divide the image into some
blocks, and propose an image reconstruction method based on block compressing sensing with
Orthogonal Matching Pursuit. By adding some simulated speckle noise in the SAR image, the
performance of the proposed approach is shown and compared with a conventional algorithm. the
result has been shown that our method can get better result in terms of peak signal noise ratio (PSNR).
Multiple Input Multiple Output- MIMO Radar is a fast growing research area. This paper will give a brief
introduction to the subject as well as derive an image formation scheme. The general problem of radar imaging
is to use some physical model for a transmitted signal, and measurements of the signal that is scattered back to
a receiver by a scene to attempt to derive information about the scene. The concept of communication involves
a message sender, a message receiver, and a channel. The sender sends a message through the channel to the
receiver. The receiver attempts to recover the original message. MIMO communication is just communication
that involves sending several messages to several recipients. The problem of Multiple Input Multiple Output
Radar Imaging is to use the corruption of transmitted messages to try and derive useful information about the
environment that the messages traveled through. The extra information gained with MIMO Radar can be used
to get rid of false targets, detect moving targets, and create a better resolution image. The plan for this research
is to culminate to an in-scene 3-d Image reconstruction algorithm. The model presented provides a context in
which to examine this problem.
This paper presents a 3D ltered inversion scheme for turntable inverse synthetic aperture radar (ISAR) data
from a scalar wave equation model. The proposed inversion scheme targets at the use of ltered back projection
(FBP) and convolution back projection (CBP) imaging algorithms. In the paper, we also provide a derivation
of a general imaging lter for the near-elds FBP and CBP imaging algorithms.