Abstract
Imaging of maneuvering targets has become a challenging topic recently. This study proposes an improved MUSIC-based single-snapshot imaging method for OFDM-MIMO radar. At the transmitter part, for orthogonal waveform generation, the interleaved OFDM structure is developed that each transmitter only radiates at an equidistant set of OFDM subcarriers unique to itself. At the receiver part, a novel preprocessing scheme is presented to separate multiple transmit/receive paths and compensate the reference point. Preprocessed echo matrix can fit the model of two-Dimensional (2D) MUSIC algorithm, except for the coupling between radial/cross-range in the virtual antenna array. Correspondingly, we modify the 2D ElementSpace (ES)-MUSIC. In the meantime, a 2D Reduced-Dimension BeamSpace Unitary-MUSIC (RD-BS-UMUSIC) algorithm is proposed for computational complexity reduction and estimation performance enhancement. Numerical results of a simulated target consists of limited number of scatterers and a complex target (a Boeing 737-800 plane) verify that the proposed algorithm can improve the imaging quality and reduce computational complexity effectively compared with the traditional method.
Highlights
The radar imaging technique provides sufficient information for target feature extraction and recognition
In [23], the radial-range image was obtained by Fast Fourier Transform (FFT), whereas in each radial-range unit, the MUltiple SIgnal Classification (MUSIC) algorithm was applied for high azimuth resolution that breaks the Rayleigh criterion
In this paper, we have formulated the imaging model of Orthogonal Frequency Division Multiplexing (OFDM)-Multiple Input Multiple Output (MIMO) radar and derived super-resolution imaging method based on 2D reduced dimension (RD)-BS-UMUSIC
Summary
The radar imaging technique provides sufficient information for target feature extraction and recognition. The MUltiple SIgnal Classification (MUSIC) algorithms [33]–[37], most frequently used for angle estimation, were recently applied in Through-the-Wall Imaging (TWI) [38], MIMO radar [23], [25], [26] and ISAR [39] for azimuth imaging due to its super-resolution ability In these works, the radial-range profile was firstly retrieved computing FFT. In [23], the radial-range image was obtained by FFT, whereas in each radial-range unit, the MUSIC algorithm was applied for high azimuth resolution that breaks the Rayleigh criterion This method may lose some inherent coupling information between two directions.
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