Prof. Rick S. Blum
Prof. Rick S. Blum, Lehigh University, USA
Biography:
Rick S. Blum received a B.S. in Electrical Engineering from the Pennsylvania State University in 1984 and his M.S. and Ph.D in Electrical Engineering from the University of Pennsylvania in 1987 and 1991.
From 1984 to 1991 he was a member of technical staff at General Electric Aerospace in Valley Forge, Pennsylvania and he graduated from GE`s Advanced Course in Engineering. Since 1991, he has been with the Electrical and Computer Engineering Department at Lehigh University in Bethlehem, Pennsylvania where he is currently a Professor and holds the Robert W. Wieseman Chaired Research Professorship in Electrical Engineering. His research interests include signal processing for communications, sensor networking, radar and sensor processing. He is on the editorial board for the Journal of Advances in Information Fusion of the International Society of Information Fusion. He was an associate editor for IEEE Transactions on Signal Processing and for IEEE Communications Letters. He has edited special issues for IEEE Transactions on Signal Processing, IEEE Journal of Selected Topics in Signal Processing and IEEE Journal on Selected Areas in Communications. He is a member of the SAM Technical Committee (TC) of the IEEE Signal Processing Society. He was a member of the Signal Processing for Communications TC of the IEEE Signal Processing Society and is a member of the Communications Theory TC of the IEEE Communication Society. He was on the awards Committee of the IEEE Communication Society.
Dr. Blum is a Fellow of the IEEE, an IEEE Third Millennium Medal winner, a member of Eta Kappa Nu and Sigma Xi, and holds several patents. He was awarded an ONR Young Investigator Award in 1997 and an NSF Research Initiation Award in 1992. His IEEE Fellow Citation "for scientific contributions to detection, data fusion and signal processing with multiple sensors" acknowledges some early contributions to the field of sensor networking.
Title: MIMO Radar with Distributed Antennas
Abstract:
Inspired by recent advances in multiple-input multiple-output (MIMO) communications, this tutorial introduces the widely spread antenna MIMO radar concept. MIMO systems have had great impact on wireless communications. The signal model for MIMO radar with distributed antennas bears similarities to the communications signal model, suggesting the possibility of interesting cross-fertilization of ideas between MIMO communications and MIMO radar. We will demonstrate that complex targets contain a large number of scatterers that result in diverse RCS patterns as a function of aspect angle. We will specify the conditions for decorrelation of the elements of the channel matrix in terms of separation between antennas, target size, target range, and carrier wavelength. We will discuss parallels to MIMO communication, in particular the similar roles that the transmission medium (channel) and target play in respectively, communication and radar. We will show that combining target returns resulting from independent illuminations yields a diversity gain akin to the diversity gain obtained in the communication problem over fading channels when the data is transmitted through independent channels. We will develop the optimal detectors for MIMO radar, and for comparison, for other radar architectures. For very widely spaced antennas, optimal processing combines sensor outputs non-coherently. From the non-coherent combination of sensor outputs, we will switch to MIMO radar with coherent processing of sensor outputs. We will show that MIMO radar can locate targets with high resolution and can resolve between closely spaced targets. The Cramer-Rao lower bound on the achievable accuracy will be discussed, and it will be shown to depend on both the carrier frequency and the sensors' locations.
