Development of a new software-defined S-band radar and its use in the test of wavelet-based waveforms

Abstract

A new software-defined S-band radar (SDSR) has recently been developed at the Air Force Research Laboratory. The system is built upon individual off-the-shelf components, devices, and instruments, and the center of the architecture is an Arbitrary Waveform Generator (AWG). The AWG can be programmed to generate various kinds of radar waveforms, which are mixed with a carrier to create Sband radar signals. The AWG can be interfaced with a computer which runs on MatLab or LabView for software definition of radar waveforms. Furthermore, the computer can be connected to the Internet for receiving data from remote users. As a result, the new SDSR can be used to support studies of radar waveforms in a large area by remote users. The characteristics of the radar system are studied and the performance of the system is optimized by selecting the parameters of the building components. The newly developed SDSR is used to test the wavelet-based radar waveforms, which verifies the theoretical results produced earlier.

Wideband Radio Frequency Noiselet Waveforms for Multiresolution Nondestructive Testing of Multilayered Structures

“…Reflected radar waveforms were decoded using an inverse WT to produce a high range resolution profile of the target. A software defined radar wherein a wavelet signal was generated by an arbitrary waveform generator and upconverted to RF was tested successfully [17]. Wavelet-based radar waveforms have been investigated for several applications, including adaptive radar [18], range sidelobe suppression [19], detection of moving targets [20], synthetic aperture radar [21], and simultaneous high resolution in range and velocity [22].…”

On the doppler effect to the wavelet-based radar waveform

“…The study reveals that WBW can suppress sidelobes to the noise level, thus resulting in better range resolution than traditional linear frequency modulated (LFM) waveforms [2]. In addition, the unique time-frequency localization property of wavelet can benefit the development of cognitive radar [1,3].…”