What are the emerging technologies and trends in radar clutter and interference mitigation?

1 Adaptive beamforming

Adaptive beamforming is a technique that allows the radar to adjust the shape and direction of its transmit and receive beams based on the environment and the target characteristics. By steering the beam towards the target and away from the clutter and interference sources, adaptive beamforming can enhance the signal-to-noise ratio (SNR) and the resolution of the radar. Adaptive beamforming can also exploit the spatial diversity of multiple antennas or array elements to suppress the interference and clutter from different directions.

2 Cognitive radar

Cognitive radar is a concept that applies the principles of artificial intelligence (AI) and machine learning (ML) to the radar system, enabling it to learn from the data, adapt to the situation, and optimize its performance. Cognitive radar can use feedback loops, reinforcement learning, and deep learning to dynamically adjust its parameters, such as frequency, waveform, bandwidth, and polarization, based on the target and the environment. Cognitive radar can also use prior knowledge, context awareness, and situational understanding to improve its clutter and interference mitigation capabilities.

3 Waveform diversity

Waveform diversity is a technique that uses different types of waveforms or modulation schemes to transmit and receive the radar signals, such as linear frequency modulation (LFM), phase-coded, frequency-hopping, or orthogonal frequency division multiplexing (OFDM). Waveform diversity can increase the information content, the spectral efficiency, and the robustness of the radar signals, as well as reduce the probability of detection and interception by the adversary. Waveform diversity can also help the radar to cope with different types of clutter and interference, such as Doppler, range, or angle spread, by exploiting the waveform characteristics or properties.

4 Compressive sensing

Compressive sensing is a technique that leverages the sparsity or structure of the radar signals or scenes to reduce the amount of data acquisition, processing, and transmission. Compressive sensing can use sub-Nyquist sampling, random projection, or sparse recovery algorithms to reconstruct the radar signals or images from a small number of measurements, thus saving time, energy, and bandwidth. Compressive sensing can also improve the clutter and interference mitigation performance by enhancing the resolution, removing the noise, and recovering the missing information.

5 Quantum radar

Quantum radar is a technique that uses quantum physics and quantum information to generate, manipulate, and measure the radar signals, such as entangled photons or squeezed states. Quantum radar can potentially offer advantages over conventional radar, such as higher sensitivity, lower noise, greater stealth, and faster processing. Quantum radar can also overcome some of the limitations or challenges of conventional radar, such as jamming, spoofing, or decoys, by exploiting the quantum features or phenomena, such as quantum correlation, quantum superposition, or quantum interference.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?