Multiple-input And Multiple-output Synthetic Aperture Radar Research Articles

MIMO-SAR: A Hierarchical High-Resolution Imaging Algorithm for mmWave FMCW Radar in Autonomous Driving

Millimeter-wave radars are being increasingly integrated into commercial vehicles to support advanced driver-assistance system features. A key shortcoming for present-day vehicular radar imaging is poor azimuth resolution (for side-looking operation) due to the form factor limits on antenna size and placement. In this paper, we propose a solution via a new multiple-input and multiple-output synthetic aperture radar (MIMO-SAR) imaging technique, that applies coherent SAR principles to vehicular MIMO radar to improve the side-view (angular) resolution. The proposed 2-stage hierarchical MIMO-SAR processing workflow drastically reduces the computation load while preserving image resolution. To enable coherent processing over the synthetic aperture, we integrate a radar odometry algorithm that estimates the trajectory of ego-radar. The MIMO-SAR algorithm is validated by both simulations and real experiment data collected by a vehicle-mounted radar platform.

High-Performance Anti-Retransmission Deception Jamming Utilizing Range Direction Multiple Input and Multiple Output (MIMO) Synthetic Aperture Radar (SAR).

Retransmission deception jamming seriously degrades the Synthetic Aperture Radar (SAR) detection efficiency and can mislead SAR image interpretation by forming false targets. In order to suppress retransmission deception jamming, this paper proposes a novel multiple input and multiple output (MIMO) SAR structure range direction MIMO SAR, whose multiple channel antennas are vertical to the azimuth. First, based on the multiple channels of range direction MIMO SAR, the orthogonal frequency division multiplexing (OFDM) linear frequency modulation (LFM) signal was adopted as the transmission signal of each channel, which is defined as a sub-band signal. This sub-band signal corresponds to the transmission channel. Then, all of the sub-band signals are modulated with random initial phases and concurrently transmitted. The signal form is more complex and difficult to intercept. Next, the echoes of the sub-band signal are utilized to synthesize a wide band signal after preprocessing. The proposed method will increase the signal to interference ratio and peak amplitude ratio of the signal to resist retransmission deception jamming. Finally, well-focused SAR imagery is obtained using a conventional imaging method where the retransmission deception jamming strength is degraded and defocused. Simulations demonstrated the effectiveness of the proposed method.

MIMO SAR Waveform Separation Based on Costas‐LFM Signal and Co‐arrays for Maritime Surveillance

In case of bright targets over a dark background, the cross-correlation noise of Multiple input and multiple output (MIMO) Synthetic aperture radar (SAR) orthogonal waveforms in the same frequency coverage will increase which can degrade the image. An Interpulse Costas hopping and intra-pulse Slope coded linearly frequency modulated (IPC-SCLFM) waveform is designed and analyzed to decrease the autocorrelation and cross-correlation noise. Besides a novel acquisition mode of “MIMO Coprime SAR” (MIMO-Cop SAR) is proposed with Coprime arrays (Co-arrays) in receive across the SAR line of flight based on digital beamforming. An improved processing by multiplying values at each pixel of two coarrays images is proposed to suppress the cross-correlation noise. MIMO-Cop SAR can effectively suppress the crosscorrelation noise, reduce the amount of data to be stored and get high signal-to-noise ratio in a simple way. The effectiveness of MIMO-Cop SAR for maritime surveillance is demonstrated by the simulation experiments.

Multiple input and multiple output synthetic aperture radar multiple waveform separation based on oblique projection in same frequency coverage

In multiple input and multiple output synthetic aperture radar (MIMO-SAR) the unwanted cross-correlation output sexist inevitably in the superposed echoes of multiple transmitted orthogonal waveforms in the same frequency coverage, which may deteriorate the quality of the reconstructed SAR image because of the high synthetic integrated sidelobe level (SISL). In this study, a novel signal decomposition based on oblique projection (SDOP) method is proposed to suppress the cross-correlation outputs. At first, the superposed echo of each receiver is modelled as a linear-combined vector of transmitted multiple waveforms. Then, the echo of each transmitted waveform is obtained by signal decomposition on the combined vector via SDOP, respectively. Besides, two new metrics, that is, synthetics integrated sidelobe level ratio improved factor and integrated sidelobe level ratio loss factor, are also proposed to assess the separation performance. It is found that the cross-correlation can be effectively suppressed among multiple waveforms via low-complexity projection operators and the output signal noise ratio can be remarkably improved, accordingly. Finally, the numerical experiments are also provided to demonstrate the effectiveness of the proposed method.

MIMO-SAR waveforms separation based on virtual polarization filter

The unwanted coupling exists inevitably among multiple orthogonal waveforms in a same frequen- cy area for multiple-input and multiple-output synthetic aperture radar (MIMO-SAR). In this paper, a new polarized MIMO-SAR model is established with two transmitting antennas and multiple receiving antennas at first. Then, a virtual polarization filter (VPF) is proposed to separate superposed returns caused by multiple transmitted waveforms based on detection on the polarized parameters via particle swarm optimizer (PSO). Compared with the conventional matched filter to separate the orthogonal waveforms, it is shown that the coupling noises can be significantly suppressed by the proposed VPF-based method and the orthogonality is not necessary among different transmitting waveforms. Finally, experimental data experiments are also provided to demonstrate the effectiveness of the proposed method.

Research on Sub-Band Synthesis Algorithm of MIMO-SAR

Multiple-Input and Multiple-Output Synthetic Aperture Radar (MIMO-SAR) can achieve high resolution and wide swath at the same time, which has a wide horizon of development in the future. An azimuth frequency-diversity MIMO-SAR is presented, and overlapped effective phase center sampling is obtained while the pulse repetition frequency (PRF) is appropriate. This paper derives an improved sub-band synthesis algorithm which reduces the complexity of conventional sub-band synthesis algorithms and improves the range resolution. The feasibility of this imaging algorithm is proved by point target simulation experiments.

MIMO‐SAR waveform separation based on inter‐pulse phase modulation and range‐Doppler decouple filtering

The coupling among multiple coded orthogonal waveforms occupying the same frequency band may seriously affect the distributed terrain imaging of multiple-input and multiple-output synthetic aperture radar (MIMO-SAR). Based on the inter-pulse phase modulation among different transmitting waveforms, a range-Doppler decouple filtering method is presented to separate waveforms effectively. Finally, numerical experiments are provided to demonstrate the effectiveness of the proposed method.

MIMO SAR using Chirp Diverse Waveform for Wide-Swath Remote Sensing

Synthetic aperture radar (SAR) is a well-proven remote sensing technique; however, current single-antenna SAR systems cannot fulfill the increasing demands of future remote sensing in high-resolution and wide-swath imaging performance. This paper presents a scheme of multiple-input and multiple-output (MIMO) SAR using chirp diverse waveform for wide-swath remote sensing. This approach employs MIMO antenna configuration in elevation which is divided into multiple subpertures. In this way, multiple pairs of transmit-receive virtual beams directing to different subswathes are formed simultaneously. Equivalently a large swath is synthesized. The corresponding system scheme, chirp diverse waveform design, multi-beam forming algorithm and range ambiguity performance are investigated. A chirp-scaling-based image formation algorithm is presented to focus the MIMO SAR simulation data. Comprehensive numerical simulation examples are performed. It is shown that the proposed method enables the SAR systems to operate with high flexibility and reconfigurability which is particularly attractive for next generation remote sensing technique.

Space–Time Coding MIMO-OFDM SAR for High-Resolution Imaging

Multiple-input and multiple-output (MIMO) radar has received renewed attention in recent years, but little work on MIMO synthetic aperture radar (SAR) remote sensing has been reported. This paper presents a scheme of space-time coding MIMO orthogonal frequency division multiplexing (OFDM) SAR for high-resolution imaging. This system employs MIMO configuration in the elevation direction and the Alamouti space-time coding scheme in the azimuth direction, along with the use of OFDM waveform diversity and displaced phase center antenna (DPCA) techniques. As an orthogonal transmission waveform is required for this novel space-time coding MIMO-OFDM SAR system, one kind of OFDM linearly frequency modulated waveforms is investigated. The matched filtering and multibeam forming in the elevation direction are detailed. Additionally, the corresponding mathematical relations and signal models for high-resolution imaging are formed. In this way, efficient spatial diversity gain and improved range resolution are obtained by the MIMO configuration, and the requirement of pulse repeated frequency for wide-swath remote sensing is reduced by the DPCA technique. The feasibility is validated by numerical simulation results.