MIMO Radar Waveform Design and Signal Processing

Multiple-input multiple-output (MIMO) radar systems employ arrays of transmit and receive elements to exploit spatial and waveform diversity for enhanced target detection, resolution and parameter estimation. By transmitting distinct or orthogonal waveforms across elements, MIMO radar achieves improved angular discrimination, increased degrees of freedom in waveform design, and resilience against interference. Recent progress has centred on the optimisation of waveform parameters under practical constraints such as constant modulus, similarity to reference signals, spectral occupancy and low probability of intercept. Advanced signal processing techniques—including adaptive filtering, compressive sensing and deep learning—have been integrated to jointly design transmit waveforms and receive filters, maximising signal-to-interference-plus-noise ratio and mitigating ambiguities. Applications range from automotive and polarimetric radar to covert surveillance and defence systems demanding ultra-low sidelobe levels and robust target detection in cluttered environments.

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Research from all publishers

Innovative optimisation algorithms have been proposed to generate mutually orthogonal MIMO waveforms by directly minimising autocorrelation and cross-correlation sidelobes. One approach employs an intelligent ions motion framework to navigate the non-convex design space, yielding polyphase codes with superior orthogonality and rapid convergence. In polarimetric radar applications, joint design of transmit polarimetric waveforms and receive filters under unit-modulus and similarity constraints has been shown to maximise average signal-to-interference-plus-noise ratio across target aspect angles, utilising alternating optimisation and closed-form updates via the alternating direction method of multipliers. To enhance low probability of intercept and detection performance, hybrid coding schemes combine complementary phase-coding with optimised discrete frequency-coding on linear frequency-modulated carriers, resulting in ultra-low sidelobe “pushpin” ambiguity functions, wide time-bandwidth products and improved stealth characteristics.

MIMO Radar Waveform Design and Signal Processing publication trend

The graph below shows the total number of articles in mimo radar waveform design and signal processing across all publications each year (not limited to Nature Index journals).

Technical terms

MIMO radar: A radar architecture using multiple transmit and receive antennas to exploit spatial diversity and waveform diversity for improved detection and parameter estimation.

Waveform diversity: The use of distinct or orthogonal transmit signals across multiple channels to enhance resolution, interference mitigation and parameter identifiability.

Orthogonality: A property of waveforms whose cross-correlation is minimised, enabling separation of signals at the receiver and reducing mutual interference.

Ambiguity function: A two-dimensional measure of waveform performance characterising range and Doppler resolution and sidelobe behaviour.

Sidelobe: Secondary peaks in the ambiguity function outside the mainlobe, whose reduction is crucial for target detection and clutter suppression.

References

1. A Novel MIMO Radar Orthogonal Waveform Design Algorithm Based on Intelligent Ions Motion. Remote Sensing (2021).
2. Constant-Modulus Waveform Design With Polarization-Adaptive Power Allocation in Polarimetric Radar. IEEE Transactions on Signal Processing (2023).
3. Ultra-Low Sidelobe Waveforms Design for LPI Radar Based on Joint Complementary Phase-Coding and Optimized Discrete Frequency-Coding. Remote Sensing (2022).