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• Develop a deep learning based object detector on radar and camera data fusion.
• Employ YOLOv8 object detector for radar and camera target detection individually.
• Apply Adam optimizer with BiLSTM model to classify detected objects.

Object detection, the process of detecting and classifying objects within a given environment, forms the foundational element. Multisensory fusion incorporates data from diverse sensors, like radar and cameras, to refine the reliability and ...

This work introduces a novel detector, bounded false-alarm rate (BFAR), for distinguishing true detections from noise in radar data, leading to improved accuracy in radar odometry estimation. Scanning frequency-modulated continuous wave (FMCW) ...$_{}^{}$$_{}^{}$$_{}^{}$$_{}^{}$

In this paper, we consider adaptations of Monte Carlo Search methods on binary decision trees where actions are simulated using heuristics and where choices are made deterministically or stochastically. We explain how these adaptations are fitted ...

In the field of distributed multi-station radar non-coherent fusion detection, the number of effective local statistics set based on hard rules does not match the actual number of that, which easily leads to unstable detection performance of the ...

Recently, deep learning-based precipitation nowcasting has been investigated and its usefulness has been recognized. However, existing approaches have treated precipitation nowcasting as a spatiotemporal sequence prediction problem and have ...

• A deep neural network using radar reflectivity and ERA5 reanalysis data was proposed to improve precipitation nowcasting.
• Nowcasting performance of deep learning-based models was analyzed in a quantitative and qualitative manner.
• ...

The integration of sensor data is crucial in the field of robotics to take full advantage of the various sensors employed. One critical aspect of this integration is determining the extrinsic calibration parameters, such as the relative ...

• A novel mm-wave radar-based mass flow sensor for monitoring mass flow rate of pneumatically conveyed peanuts was developed.
• Testbeds based on 2-row and 6-row peanut combines were developed to generate different peanut mass flow rates ...

A millimeter-wave FMCW radar-based mass flow sensor was developed and evaluated to monitor peanut mass flow rate towards development of a peanut yield monitor. The radar sensor components were placed outside a customized plastic duct in the ...

External disturbances, such as interference, have a significant impact on the functionality of radio detection and ranging (radar) systems, which are employed for the identification, ranging, and imaging of target objects. As radar systems are ...

Everyday, billions of people use footwear for walking, running, or exercise. Of emerging interest are “smart footwear”, which help users track gait, count steps or even analyse performance. However, such nascent footwear lack fine-grain ground surface ...

A wearable millimetre-wave radar antenna operating in 24.05–24.25 GHz for imaging applications in collision avoidance to assist visually impaired people is presented. Non-uniform excitation for the series end-fed 1 × 10 array antenna is optimized ...

Millimeter wave sensing has rapidly gained prominence with the advent of Frequency Modulated Continuous Wave (FMCW) radars, redefining applications in both indoor and outdoor domains. An emerging focus in this field revolves around developing intelligent ...

Ground based radar is a key system for aerial defence of any country. Current generations of radar use Moving Target Indicator (MTI) filter, Constant False Alarm Rate (CFAR) and Peak Detection (PD) algorithms for detection of target ...

In many industrial or healthcare contexts, keeping track of the number of people is essential. Radar systems, with their low overall cost and power consumption, enable privacy-friendly monitoring in many use cases. Yet, radar data are hard to ...

• Based on matched filter outputs, RIAF-IDS reduces the computational complexity.

Recently, a two-dimensional joint iterative adaptive filtering (2-D JIAF) has been proposed to address the masking effect of large targets on adjacent small targets in multi-target scenarios. However, its performance is impaired for ...

In this paper, we consider a monostatic radar receiver for a joint communication and radar (JCR) system that transmits orthogonal time frequency space (OTFS) frames for target detection and parameter estimation. The circular prolate ...

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• PAPR characteristics of the CPPS OTFS waveform is studied.
• Modelling of the ...

In this paper, the design of phase-coded sequences with good aperiodic autocorrelation properties including peak sidelobe level and integrated sidelobe level for radar systems is considered. The problem is formulated as a rank-one ...

The performance of perception systems developed for autonomous driving vehicles has seen significant improvements over the last few years. This improvement was associated with the increasing use of LiDAR sensors and point cloud data to facilitate ...

Deep learning models such as deep convolutional neural networks (DCNNs) image classifiers have achieved outstanding performance over the last decade. However, these models are mostly trained with high-quality images drawn from publicly available ...

In the last decade, the low cost and easy availability of Unmanned Aerial Vehicles (UAVs) have led to their enormous use in modern society, which leads to privacy and security issues. To keep an eye on the intruder UAV in the ...

The detection of human motion is receiving more attention amongst researchers, and is important in several applications. However, the issue is to offer effective monitoring sensors amongst various platforms without diminishing privacy. The radar ...