Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Radar Array Processing
Distributed beamforming for information transfer in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Convex Optimization
Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
Target Detection and Localization Using MIMO Radars and Sonars
IEEE Transactions on Signal Processing
Time-Slotted Round-Trip Carrier Synchronization for Distributed Beamforming
IEEE Transactions on Signal Processing
Spatial diversity in radars-models and detection performance
IEEE Transactions on Signal Processing
MIMO Radar Ambiguity Properties and Optimization Using Frequency-Hopping Waveforms
IEEE Transactions on Signal Processing
Cramer-Rao bounds for estimating range, velocity, and directionwith an active array
IEEE Transactions on Signal Processing
Analysis of wireless geolocation in a non-line-of-sight environment
IEEE Transactions on Wireless Communications
Finite-sample optimal joint target detection and parameter estimation by MIMO radars
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
A MIMO radar system approach to target tracking
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Performance and complexity issues in noncoherent and coherent MIMO radar
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Optimal point target detection with unknown parameters by MIMO radars
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Noncoherent MIMO radar for location and velocity estimation: more antennas means better performance
IEEE Transactions on Signal Processing
Space-time coding for MIMO radar detection and ranging
IEEE Transactions on Signal Processing
Direct positioning of stationary targets using MIMO radar
Signal Processing
Robust power allocation for energy-efficient location-aware networks
IEEE/ACM Transactions on Networking (TON)
Hi-index | 754.84 |
This paper presents an analysis of target localization accuracy, attainable by the use of multiple-input multiple-output (MIMO) radar systems, configured with multiple transmit and receive sensors, widely distributed over an area. The Cramer-Rao lower bound (CRLB) for target localization accuracy is developed for both coherent and noncoherent processing. Coherent processing requires a common phase reference for all transmit and receive sensors. The CRLB is shown to be inversely proportional to the signal effective bandwidth in the noncoherent case, but is approximately inversely proportional to the carrier frequency in the coherent case. We further prove that optimization over the sensors' positions lowers the CRLB by a factor equal to the product of the number of transmitting and receiving sensors. The best linear unbiased estimator (BLUE) is derived for the MIMO target localization problem. The BLUE's utility is in providing a closed-form localization estimate that facilitates the analysis of the relations between sensors locations, target location, and localization accuracy. Geometric dilution of precision (GDOP) contours are used to map the relative performance accuracy for a given layout of radars over a given geographic area.