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This article develops the multiple-input multiple-output (MIMO) technology for weather radar sensing. There are ample advantages of MIMO that have been highlighted that can improve the spatial resolution of the observations and also the accuracy of the radar variables. These concepts have been introduced here pertaining to weather radar observations with supporting simulations demonstrating improvements to existing phased array technology. Already MIMO is being used in a big way for hard target detection and tracking and also in the automotive radar industry and it offers similar improvements for weather radar observations. Some of the benefits are discussed here with a phased array platform in mind which offers quadrant outputs.
In this paper, we describe the evolution of a pair of polyphase coded waveform for use in second trip suppression in weather radar. The polyphase codes were designed and tested on NASA weather radar. The NASA dual-frequency, dual-polarization Doppler
Subspace methods are essential to high-resolution environment sensing in the emerging unmanned systems, if further combined with the millimeter-wave (mm-Wave) massive multi-input multi-output (MIMO) technique. The estimation of signal/noise subspace,
Millimeter-wave (mmWave) radars are being increasingly integrated in commercial vehicles to support new Adaptive Driver Assisted Systems (ADAS) features that require accurate location and Doppler velocity estimates of objects, independent of environm
This paper investigates the hybrid precoding design for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems with finite-alphabet inputs. The precoding problem is a joint optimization of analog and digital precoders, and we treat it
In this paper we presented mmPose-NLP, a novel Natural Language Processing (NLP) inspired Sequence-to-Sequence (Seq2Seq) skeletal key-point estimator using millimeter-wave (mmWave) radar data. To the best of the authors knowledge, this is the first m