Abstract
Multi-input and multi-output (MIMO) radar systems possess numerous advantages, such as scanning an entire region much faster than a phased array, enhancing the spatial resolution, mitigating interference and multipath fading, and improving the probability of detection of targets. MIMO radar systems use adaptive beamforming techniques such as the minimum variance distortionless response (MVDR) to obtain the best possible estimation of the direction of arrival (DOA) of the targets. The MVDR algorithm has been thoroughly investigated for traditional phased array radars. For MIMO radar systems, however, it requires significant signal processing, which can introduce substantial latency, especially in the case of large MIMO systems where few hundred antennas are used; this can be solved by using a Graphics Processor Unit (GPU), which contains thousands of cores and can execute many operations in parallel. This paper presents a MATLAB-based approach for GPU parallelization of the minimum variance distortionless (MVDR) beamforming algorithm in a MIMO radar system. Two MIMO radar systems are considered. The first one is a simulated MIMO radar which is used for automotive adaptive cruise control (ACC), and the second one is an experimental monostatic MIMO radar that is based on a vector network analyzer (VNA). It is shown that the GPU achieved a speedup of up to 7 times while successfully detecting all targets.
Highlights
The application of multi-input and multi-output (MIMO) techniques to radar systems has received considerable attention recently [1,2,3,4,5,6,7,8,9,10,11,12,13]
The first one is a simulated MIMO radar, which is used for automotive adaptive cruise control (ACC) [14] and the second one is an experimental monostatic MIMO radar that is based on a vector network analyzer (VNA) [15]
This paper explores the use of Graphics Processor Unit (GPU) technology in a traditional
Summary
The application of multi-input and multi-output (MIMO) techniques to radar systems has received considerable attention recently [1,2,3,4,5,6,7,8,9,10,11,12,13]. In a MIMO radar with collocated antennas, the antenna elements are closely spaced so that each transmit-receive pair sees the same aspect of the target While this configuration does not provide spatial diversity, it relies on waveform diversity to achieve a better spatial resolution by combining all the transmitting paths in a virtual array with an extended aperture. It consists of a simulated automotive MIMO radar that is used for adaptive cruise control (ACC) onboard an autonomous vehicle that tracks two moving vehicle targets [27] The simulation of this system is performed using the Phased Array Toolbox (PAT) of MATLAB [28], and the GPU acceleration of the MVDR algorithm is performed using the Parallel Computing Toolbox (PCT) [29].
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