DETECTION AND ESTIMATION IN ULTRAWIDEBAND MIMO NOISE RADAR

Open Access
Author:
Chen, Wei-Jen
Graduate Program:
Electrical Engineering
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
May 03, 2010
Committee Members:
  • Ram Mohan Narayanan, Dissertation Advisor
  • Ram Mohan Narayanan, Committee Chair
  • John F Doherty, Committee Member
  • Julio Urbina, Committee Member
  • Soundar Rajan Tirupatikumara, Committee Member
Keywords:
  • TDL BEAMFORMING
  • MIMO
  • ULTRAWIDEBAND
  • GENERALIZED LIKELIHOOD RATIO TEST
Abstract:
In radar systems, the wider the bandwidth, the better is the range resolution. While a variety of transmit waveforms can be used, noise and noise-like waveforms are preferred from the standpoint of covertness and immunity to jamming and interference. Moreover, multi-input-multi-output (MIMO) spatial diversity radar significantly improves radar detection and estimation performances. Based to the above advantages, ultrawideband (UWB) MIMO noise radar systems are garnering more and more attention recently. In this dissertation, two issues concerning detection and estimation in UWB MIMO noise radar are investigated in detail. First, we consider the problem of estimating target directions in UWB MIMO noise radar. In our system, transmitters are sufficiently separated and transmit UWB independent noise waveforms to satisfy the requirements of MIMO spatial diversity. Receivers are assumed to be spaced half-wavelength apart to eliminate directional ambiguity. We apply the tapped-delay line (TDL) based beamforming technique to concentrate on receiving signals from a certain direction, and to efficiently suppress the interferences from the others. According to the TDL outputs, the CLEAN-sense conditional generalized likelihood ratio test (CGLRT) is applied for detecting the targets given the average of the square of the absolute value of the residual signal resulting from the CLEAN algorithm. Then, we propose a new mechanism called the iterative CGLRT (ICGLRT) to determine their directions by implementing these two techniques iteratively. Simulation results show that ICGLRT is able to sequentially detect the targets and improve target direction estimation accuracy even when their reflections are seriously interfered with by others. Then, with some simplifications to the system model, we analyze the mean square error (MSE) of target velocity and location estimation in UWB MIMO noise radar. The ambiguity function (AF) formulation is applied to implement the estimations. Since the maximum of the AF is attained when the time-delay and Doppler stretch of replica signals are exactly matched with the ones corresponding to the reflections, this estimation is also a peak localization problem. When noise is added, the peak may be located in a different place causing error. In this dissertation, we develop probability density functions (pdfs) to approximate the distributions of coherent and non-coherent ambiguity functions (CAFs and NCAFs) and apply the pdfs to analyze MSE of their estimates. Based on the analyses, we explain and demonstrate that the NCAF is the better estimation approach in spatial diversity MIMO radar. Finally, the error floor resulting from NCAF approach is further discussed.