Much work has been done designing transmit waveforms for target identification, classification, and detection. In addition, these have also been studied in both single and multiple-antenna scenarios. In this work, we study the construction of a waveform when multiple radar sensors are used to image a target scene. The scene is assumed to have a prior distribution given by a Compound Gaussian (CG) - a model that has proven very useful in the field of image processing. Waveform optimization is done with the objective of optimizing mutual information, while reconstruction was performed using sparsity based reconstruction techniques. In our work, the waveform is tailored for a particular target of interest in the scene while suppressing the clutter. Using our waveform techniques, we demonstrate statistically significant improvements in the quality of the reconstructed image in peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM). We validate our algorithms using the MSTAR database.
The energy allocation of a transmit waveform ultimately dictates the effectiveness by which it extracts a target in a cluttered environment. The quantification of information present in the radar cross section offers notable advantages as a fitness function for the design of efficiently energy distributed waveforms for target identification. A robust method of suppression of both the temporal and spectral characteristics for target attenuating radar returns (clutter) is developed in this paper. By means of a priori knowledge of a target spectral response, a method of clutter mitigation for target identification using ultra-wide band (UWB) radar is developed. The robust design method takes after the Taguchi Method after and has seen growing use in biotechnology, statistics, and engineering as a method for both design and analysis. The Taguchi algorithm (TA) is created, based on an orthogonal matrix level design, in conjunction with the mutual information (MI) used as a criterion for convergence. This method efficiently allocates available resources within bins in which target spectral characteristics dominate those of which are undesired. As cognitive UWB radars constantly received clutter echoes and experience external noise sources, the mutual information is calculated adaptively during optimization between a transmit waveform given knowledge of the target, and the received waveform.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.