Paper
12 June 1996 High-performance signal characterization workstation
Author Affiliations +
Abstract
Essex has been involved in quadratic processing research and the design of processors that compute these algorithms for the past 14 years. We are developing a more efficient processor (Labyrinth-IITM) that has higher dynamic range (greater than 100 dB) and enhanced throughput (approximately 70 times faster). Labyrinth-IITM is a unique half-rack integration of non-developmental units that provides the compute power to solve complex signal processing tasks with significantly reduced latency. The architecture is a flexible combination of high-speed laser optics and digital technologies that is readily configured by the customer to perform a variety of functions. One or two signals can be input to the processor for linear or quadratic processing. The new processor is much simpler, more compact, and more flexible than predecessors. This paper presents a description of this new workstation accelerator. The functions generated by this processor are the ambiguity function, Wigner-Ville function, and cyclic spectrum. Other functions that can be represented by two signal inputs can also be generated by this accelerator. Some applications include high resolution spectral analysis, radar waveform processing, signal detection and characterization, geolocation using time and frequency differences of arrival, and direction finding using angle of arrival.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Keith R. Frampton "High-performance signal characterization workstation", Proc. SPIE 2754, Advances in Optical Information Processing VII, (12 June 1996); https://doi.org/10.1117/12.243144
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Signal processing

Radar signal processing

Optoelectronics

Doppler effect

Radar

Channel projecting optics

Digital signal processing

Back to Top