Abstract
In this article, we consider the joint estimation of direction-of-departure (DOD) and direction-of-arrival (DOA) information of maneuvering targets in a bistatic multiple-input multiple-output (MIMO) radar system that exploits spatial time-frequency distribution (STFD). STFD has been found useful in solving various array processing problems, such as direction finding and blind source separation, where nonstationary signals with time-varying spectral characteristics are encountered. The STFD approach to array processing has been primarily limited to conventional problems for passive radar platform that deals with signal arrivals, while its use in a MIMO radar configuration has received much less attention. This paper examines the use of STFD in MIMO radar systems with application to direction finding of moving targets with nonstationary signatures. Within this framework, we consider the use of joint transmit and receive apertures for the improved estimation of both target time-varying Doppler signatures and joint DOD/DOA. It is demonstrated that the STFD is an effective tool in MIMO radar processing when moving targets produce Doppler signatures that are highly localized in the time-frequency domain.
Highlights
Multiple-input multiple-output (MIMO) radar is an emerging technology that has attracted significant interest in the radar community [1,2]
Consider a bistatic MIMO radar system consisting of Nt closely spaced transmit antennas and Nr closely spaced receive antennas
Autoterm time-frequency distributions (TFDs) enhancement over crossterm In this subsection, we focus on the auto-term enhancement in the presence of cross-terms
Summary
Multiple-input multiple-output (MIMO) radar is an emerging technology that has attracted significant interest in the radar community [1,2]. The STFD matrix is related to the source TFD matrix by the spatial mixing matrix in a manner similar to the commonly used formula in array processing problems using second-order statistics that relates the sensor spatial covariance matrix to the source covariance matrix This similarity has enables eigenstructure and subspace methods to play a role in high-resolution DOA estimation of nonstationary sources. The separability of the source time-frequency signature and the flexibility in time-frequency point set selection further increase the SNR and reduce the mutual interference between the signals, yielding improved subspace robustness It allows processing more sources than the number of sensors. We develop our time-frequency domain DOD/DOA estimation technique based on the combined ESPRIT-MUSIC method [7], which only requires two decoupled one-dimensional direction finding operations where the DOD and DOA are automatically paired.
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