CiteULike: dcastros Chizhik

A wave-based wideband MIMO channel modeling technique

H Xu — 2008-02-19T08:19:21-00:00

Personal, Indoor and Mobile Radio Communications, 2002. The 13th IEEE International Symposium on, Vol. 4 (2002), pp. 1626-1630 vol.4.

The paper presents a multiple-input-multiple-output (MIMO) channel modeling technique for link level and system level simulations. The classical approach of wave superposition is adopted to generate MIMO channels that are statistically consistent in delay, frequency and angle domains. The paper proposes an efficient way to generate four dimensional MIMO channel transfer matrices based on standard channel statistics such as power delay profile (PDP) and power azimuth spectrum (PAS).

Performance of MIMO radar systems: advantages of angular diversity

E Fishler — 2008-02-19T08:18:57-00:00

Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on, Vol. 1 (2004), pp. 305-309 Vol.1.

Inspired by recent advances in multiple-input multiple-output (MIMO) communications, this paper introduces the statistical MIMO radar concept. The fundamental difference between statistical MIMO and other radar array systems is that the latter seek to maximize the coherent processing gain, while statistical MIMO radar capitalizes on the diversity of target scattering to improve radar performance. Coherent processing is made possible by highly correlated signals at the receiver array, whereas in statistical MIMO radar, the signals received by the array elements are uncorrelated. It is well known that in conventional radar, slow fluctuations of the target radar cross-section (RCS) result in target fades that degrade radar performance. By spacing the antenna elements at the transmitter and at the receiver such that the target angular spread is manifested, the MIMO radar can exploit the spatial diversity of target scatterers opening the way to a variety of new techniques that can improve radar performance. In this paper, we focus on the application of the target spatial diversity to improve detection performance. The optimal detector in the Neyman-Pearson sense is developed and analyzed for the statistical MIMO radar. An optimal detector invariant to the signal and noise levels is also developed and analyzed. In this case as well, statistical MIMO radar provides great improvements over other types of array radars.

MIMO radar: an idea whose time has come

E Fishler — 2006-05-25T18:23:25-00:00

Radar Conference, 2004. Proceedings of the IEEE (2004), pp. 71-78.

It has recently been shown that multiple-input multiple-output (MIMO) antenna systems have the potential to improve dramatically the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, target scintillations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it takes the opposite view; namely, it capitalizes on target scintillations to improve the radar's performance. We introduce the MIMO concept for radar. The MIMO radar system under consideration consists of a transmit array with widely-spaced elements such that each views a different aspect of the target. The array at the receiver is a conventional array used for direction finding (DF). The system performance analysis is carried out in terms of the Cramer-Rao bound of the mean-square error in estimating the target direction. It is shown that MIMO radar leads to significant performance improvement in DF accuracy.