Sinopsis
Recent advances in sensor technology and information processing afford a new flexibility in the design of waveforms for agile sensing. Sensors are now developed with the ability to dynamically choose their transmit or receive waveforms in order to optimize an objective cost function. This has exposed a new paradigm of significant performance improvements in active sensing: dynamic waveform adaptation to environment conditions, target structures, or information features. The manuscript provides a review of recent advances in waveform-agile sensing for target tracking applications. A dynamic waveform selection and configuration scheme is developed for two active sensors that track one or multiple mobile targets. A detailed description of two sequential Monte Carlo algorithms for agile tracking are presented, together with relevant Matlab code and simulation studies, to demonstrate the benefits of dynamic waveform adaptation. The work will be of interest not only to practitioners of radar and sonar, but also other applications where waveforms can be dynamically designed, such as communications and biosensing. Table of Contents: Waveform-Agile Target Tracking Application Formulation / Dynamic Waveform Selection with Application to Narrowband and Wideband Environments / Dynamic Waveform Selection for Tracking in Clutter / Conclusions / CRLB Evaluation for Gaussian Envelope GFM Chirp from the Ambiguity Function / CRLB Evaluation from the Complex Envelope
Acerca del autor
Sandeep P. Sira received the M.Tech. degree from the Indian Institute of Technology, Kanpur, India, in 1999, and the Ph.D. degree in electrical engineering in 2007 from Arizona State University (ASU). In 2007, he was a post-doctoral research associate at ASU. He is currently with Zounds Inc., in Mesa, Arizona. His research interests include waveform-agile sensing, target tracking, audio signal processing, and detection and estimation theory. Antonia Papandreou-Suppappola is a Professor in the Department of Electrical Engineering at Arizona State University (ASU). She is the co-Director of the Sensor, Signal and Information Processing (SenSIP) Center, and Associate Director of the Adaptive Intelligent Materials and Sys[1]tems (AIMS) Center at ASU. Her research interests are in the areas of Waveform-Agile Sensing, Time-Frequency Signal Processing, and Statistical Signal Processing. She is currently funded by an Air Force Office of Scientific Research (AFOSR) Multidisciplinary UniversityResearch Initiative (MURI) on Adaptive Waveform Design for Full Spectral Dominance, and she participated in the DARPA Waveform-Agile Sensing, program, where she worked on waveform selection algorithms for sensing in highly cluttered environments. Darryl Morrell is an associate professor of engineering at Arizona State University, where he is participating in the design and implementation of a multidisciplinary undergraduate engineer[1]ing program using innovative, research-based pedagogical and curricular approaches. His research interests include stochastic decision theory applied to sensor scheduling and information fusion as well as application of research-based pedagogy to engineering education.
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