Multiple-input and multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar with large-scale antenna array using a high bandwidth chirp signal is required to achieve high resolution radar imaging. However, the design of such a system can result in the spatial-wideband effect, which causes a major problem for the performance of radar systems. In this study, we categorize the spatial-wideband effect of MIMO FMCW radar as the range migration and the beam squint effect. Subsequently, we analyze the degradation degree of the radar performance depending on system parameters. The simulation and experimental results showed that the spatial-wideband effect in radar systems increases the half power beam width (HPBW) of the angle response and decreases the peak power. In addition, this effect gets severe with increasing chirping bandwidth, the number of antenna elements and target angle. To overcome these issues, we propose a phase compensation method with low computation complexity for real-time implementation. The performance of the proposed method was verified by evaluating the range-angle response using the commercial MIMO FMCW radar development kit. With a total of 86 uniform linear array antenna elements and a chirping bandwidth of 3.787 GHz, HPBW of a single target located at 60° was reduced from 2.24° to 1.78° and the peak power of that was enhanced by a factor of 2.05. From these observations, we expect that the proposed method mitigates the spatial-wideband effect of MIMO FMCW radar system, thereby providing the enhanced field of view and radar imaging for high-level autonomous driving systems.

This paper presents an intercarrier interference (ICI) mitigation method for orthogonal frequency division multiplexing (OFDM) radar. The effects of ICI on radar performance are analyzed according to dynamic range, peak power, and noise floor. To enhance OFDM radar performance, we propose a two-step ICI mitigation method. Coarse compensation partially restores the target's peak power distorted by ICI and estimates actual velocity of each scatterer without ambiguity. Consequently, fine compensation reconstructs the signal from each scatterer as ICI-free signal. The simulation result shows that the proposed method can restore the target's peak power to the level without Doppler shift, and the noise due to ICI effect can be reduced. Since our method is based on OFDM symbols designed for communication systems, it can eliminate ICI effect in OFDM radar without any loss of communication performance, which is preferable for joint radar-communication systems.

For the high-resolution DoA (Direction of Arrival) estimation, various multiplexing schemes are considered for the multi-input multi-output (MIMO) fast chirp frequency-modulated continuous-wave (FMCW) radar. However, current schemes such as time-division multiplexing (TDM) and binary-phase modulation (BPM) may reduce the maximum detectable velocity, which causes the velocity ambiguity problem. As an extension of the BPM scheme to mitigate this issue, we propose a novel multiplexing scheme using M phase-shift keying (MPSK) code which duplicates shifted target peaks at unequal intervals over the velocity domain. The proposed scheme finds the true peaks to resolve the velocity ambiguity problem by the inversion of the circulant matrix with low additional computation. In addition, the successful implementation of the proposed scheme is conducted with 4 by 8 MIMO uniform linear array (ULA) antennas through the state-of-the-art FMCW radar. Finally, the proposed scheme is compared to the conventional TDM based MIMO scheme regarding signal to noise ratio (SNR) and phase calibration issues for moving targets. The proposed scheme is to estimate the accurate 4D information of targets while resolving the velocity ambiguity problem in the MIMO FMCW radar systems.

Phase modulated continuous wave (PMCW) radar is one of promising options for the enhanced sensing capability and the multiple access availability. In this article, we focus on the advantage of the high-resolution multi-input multioutput (MIMO) radar with fast-time code division multiplexing (CDM). First, we formulate the signal model of the fast-time CDM-MIMO PMCW radar by assigning different code sequences to each transmitter (Tx). We investigate the level of self-code interference induced by simultaneously transmitting Tx signals, as a function of the number of Tx and the type of sequence. For self-code interference cancellation, we propose compressive sensing-based greedy algorithms with significantly reduced computation complexity using the property of the circulant matrix. We show via simulation that the proposed methods can effectively mitigate self-code interference and generate radar images by implementing virtual antenna array with significantly enhanced peak to sidelobe ratio and range/angle estimation accuracy. Since the proposed method can fully leverage the advantages of CDM whose transmit signals share time-frequency resources, it can be utilized for high density Internet of Things networks and increase the fundamental performance of sensing while the reduced computations are suitable for the real-time operation.

We present a fast acquisition method for direct-sequence spread spectrum systems. By considering sampling frequency offset, the algorithm enables higher coherent integration time and high sensitivity. The proposed algorithm is almost as fast as conventional methods, which do not consider sampling frequency offset.

Due to availability of maintaining the orthogonality between transmit signals and effectively leveraging time resources, Doppler division multiplexing (DDM) method has been widely investigated for operating multiple-input multiple-output (MIMO) radar systems. However, the number of peaks equal to the number of transmitting antenna elements appear along the velocity axis for every target, and it leads to Doppler ambiguity problem. As a solution, we propose a novel approach to resolve the Doppler ambiguity using the phase information of folded array, which overlaps certain antenna array elements when forming the entire MIMO antenna array. The proposed method consists of two main steps. First, we apply the uniform phase DDM to simultaneously transmit signals for each transmitting antenna elements. This method results in multiple peaks for the same target occurring at constant intervals along the velocity axis. By using the similarity of phase values between overlapping MIMO array elements, our proposed method can accurately determine the precise order of the transmitting antenna elements. Since the proposed method resolves Doppler ambiguity and enables to use non-coherent integration (NCI) on both the receiving and transmitting antenna channels, it significantly improves the signal-to-noise ratio (SNR) and increases the detection probability. Simulation and experimental results based on automotive radar sensor demonstrate the effectiveness of the proposed method and we expect that this method enables reliable perception tasks for autonomous driving.