Radar Paper Collection

Object Detection/Tracking Signal Processing Grid Mapping Cognitive Radar Vehicle Attitude Estimation Radar Testing Survey
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Publications
Real-time human motion behavior detection via CNN using mmWave radar

M Li, M Stolz

This paper preserves individual reflection points in assigned grid cells and employs a model-based clustering window to ensure stability and high true positive rates.

Object Detection/Tracking
Radar based object detection and tracking for autonomous driving

A Manjunath, Ying Liu, Bernardo Henriques

introduces a postprocessing architecture designed to cluster and track multiple radar detections from a single object in complex scenarios.

Object Detection/Tracking
Estimation of the orientation of vehicles In high-resolution radar images.

F Roos,Dominik Kellner, Jens Klappstein,Juergen Dickmann

Leveraging high-resolution image radars to estimate vehicle orientation swiftly in critical traffic situations. It adapts the orientated bounding box algorithm and introduces a quality function to select the optimal bounding box.

Object Detection/Tracking
A direct scattering model for tracking vehicles with high-resolution radars

C Knill, Alexander Scheel, Klaus Dietmanyer

It introduces a measurement model designed to track vehicles with rectangular shapes in various traffic scenarios, utilizing Doppler information for improved tracking.

Object Detection/Tracking
Micro-Doppler extraction of pedestrian limbs for high resolution automotive radar.

D Steinhauser, Alexander Kamann, Patrick Held

The process includes identifying pedestrian reflections, applying a CLEAN algorithm, clustering, and azimuth angle estimation. Real radar measurements are compared to motion capture references, demonstrating the ability to capture time-dependent motion behavior of various body parts, including legs, arms, and the torso.

Object Detection/Tracking
Micro-doppler based human-robot classification using ensemble and deep learning approaches.

S Abdulatif,Qian Wei, Fady Aziz

Focuses on micro-Doppler (μ-D) and micro-Range (μ-R) signatures for target classification. The study compares classical learning methods, ensemble classifiers, and a Deep Convolutional Neural Network (DCNN).

Object Detection/Tracking
Multi-sensor multi-object tracking of vehicles using high-resolution radars.

A Scheel, Christina Knill, Klaus Dietmayer

It introduces a Labeled Multi-Bernoulli filter, a probabilistic approach that exploits detailed sensor information, resolves measurement-to-object association ambiguities, and supports multi-sensor setups for redundancy and wider fields of view.

Object Detection/Tracking
Radar-based road user classification and novelty detection with recurrent neural network ensembles.

N Scheiner, Nils Appenrodt, Jurgen Dickmann

It introduces a classifier ensemble approach, enriched by one-vs-all correction classifiers, to efficiently classify traffic participants and identify hidden object classes not seen during training.

Object Detection/Tracking
Detection and Localization of Unmanned Aircraft Systems Using Millimeter-Wave Automotive Radar Sensors

P.Joseph, B.Morris and K. V. S. Hari

This letter reports the measurements and results of tests conducted on the detection of unmanned aircraft systems (UASs) or drones using a millimeter-wave (mmWave) automotive radar sensor.

Object Detection/Tracking
Micro-Doppler radar classification of humans and animals in an operational environment

W.D. van Eedena, J.P. de Villiers, R. J. Berndt, W.A.J. Nel, E. Blaschc

A combined Gaussian mixture model and hidden Markov model (HMM) is developed to distinguish between slow moving animal and human targets using mel-cepstrum coefficients.

Object Detection/Tracking
An adaptive 3D grid-based clustering algorithm for automotive high resolution radar sensor

M Li, M Stolz,Zhaofei Feng

Retains individual reflection points in different grid cells, utilizes a clustering window for similarity in three dimensions, and incorporates a model-based approach to ensure stable results with high true positive rates, regardless of parameters and object types.

Object Detection/Tracking
A fast grid-based clustering algorithm for range/Doppler/DoA measurements

T. Wagner, R. Feger, A. Stelzer

Present a grid-based clustering algorithm, which directly utilizes the gridded result of a three-dimensional fast Fourier transform.

Object Detection/Tracking
Technologies for Efficient Amateur Drone Detection in 5G Millimeter-Wave Cellular Infrastructure

D. Solomitckii, M. Gapeyenko, V. Semkin, S. Andreev, Y. Koucheryavy

In this work, we propose to exploit 5G millimeter-wave deployments to detect violating amateur drones. We argue that the prospective 5G infrastructure may provide all the necessary technology elements to support efficient detection of small-sized drones.

Object Detection/Tracking
Non-Invasive Axle-Based Vehicle Classification Utilising Tracking Radar Technology

V. R. J. Deville; C. M. Lievers; J. H. Manton

This paper demonstrates the feasibility of using tracking radar technology to provide non-invasive axle-based vehicle classification. A new algorithm that extracts the physical characteristics of the vehicle from its radar signal return is presented.

Object Detection/Tracking
Vehicle Localization using 76GHz Omnidirectional Millimeter-Wave Radar for Winter Automated Driving

K Yoneda, Naoya Hashimoto,Ryo Yanase

Radar Perception and signal filtering processing in Extreme weather.

Signal Processing
77 GHz Low-Cost Single-Chip Radar Sensor for Automotive Ground Speed Detection

T Nagasaku,Kenji Kogo, Hiroshi Shinoda

Use chip to prove 77 Ghz Radar have outstanding performance for autonomous driving. Self-designed Chip applied in this paper.

Signal Processing
Instantaneous full-motion estimation of arbitrary objects using dual Doppler radar

Dominik Kellner, Michael Barjenbruch, Jens Klappstein, Jürgen Dickmann, Klaus Dietmayer

This approach analyzes the object's velocity profile obtained from two Doppler radar sensors, reducing reaction time in safety and advanced driving assistance applications.

Signal Processing
PreCFAR Gridmaps for Automotive Radar

F. Weishaupt, N. Appenrodt, J. F. Tilly, J. Dickmann , D. Heberling

For higher levels of driving automation, presenting a radar-based method utilizing a lower data level than typical peak detection point clouds (e.g. Constant False Alarm Rate (CFAR) detection) to address some challenges in static environment perception.

Signal Processing
Radar-based Near Field Environment Perception using Back Projection Algorithm

P. Zaumseil , D. Steinhauser , P. Held , A. Kamann, T. Brandmeier

This paper presents the application of a back projection algorithm to frequency-modulated continuous wave (FMCW) radar for increasing target localization in the automotive field.

Signal Processing
Antenna Array Design for Coherent MIMO Radar Networks

V. Janoudi, P. Schoeder, T. Grebner, D. Schwarz, C. Waldschmidt J. Dickmann, N. Appenrodt

This paper presents a radar network consisting of two individual MIMO radar sensors equipped with L-shaped physical antenna arrays. Furthermore, the paper discusses the performance of the resulting virtual aperture in the context of DoA estimation.

Signal Processing
Research on the Method of Environmental Perception Based on Millimeter Wave Radar

Lei Xing; Fei Peng; Rui Pan

In order to improve the environmental perception performance of millimeter wave radar in static situation and in motion, this paper analyzed reasons for the insufficient measurement of millimeter wave radar and improved filter methods to reduce the impact of noise or environment on millimeter wave radar.

Signal Processing
High resolution automotive radar data clustering with novel cluster method

M. Stolz, M. Li, Z. Feng, M. Kunert, W. Menzel

In this paper a new approach for automotive radar data clustering is presented.

Signal Processing
Sliding-Window-Based Detection for Spectrum Sensing in Radar Bands

D. Guimarães, C. H. Lim

Present a spectrum sensing technique that combines the intermediate detections from multiple small sliding sensing windows of the received radar signal into a final decision.

Signal Processing
Adaptive-Sliding-Window-Based Detection for Noncooperative Spectrum Sensing in Radar Band

J.Noh, Y.Kwon, J.Lee, H. Baek , and J. Lim

Propose adaptive-sliding-window-based energy detection (ASED) that adaptively applies the sliding window and estimates the pulsewidth using triple thresholds

Signal Processing
Low Cost Millimetre-Wave Scale Model RCS Characterisation

N.Litov, H.Zhou and A.Mehta

Present a novel, low cost, high accuracy, high frequency radar cross section characterization method using commercially available.

Signal Processing
Doppler-spectrum feature-based human–vehicle classification scheme using machine learning for an FMCW radar sensor

E. Hyun, Y. Jin

Propose a Doppler-spectrum feature-based human–vehicle classification scheme for anFMCW(frequency-modulated continuous wave) radar sensor.

Signal Processing
Clustering of high resolution automotive radar detections and subsequent feature extraction for classification of road users

E. Schubert, F. Meinl, M. Kunert, W. Menzel

This paper copes with the clustering of all challenges into appropriate groups in order to exploit the advantages of multidimensional object size estimation and object classification

Signal Processing
3D-scattering center detection of automotive targets using 77 GHz UWB radar sensors

Markus Andres, Peter Feil, Wolfgang Menzel

3D scattering center analysis enables to derive radar system specifications for future automotive applications. Synthetic aperture radar (SAR) and SAR in combination with digital beam forming (DBF) will be presented to extract the location of scattering centers at 77 GHz.

Signal Processing
Robust Interference Cancellation for Vehicular Communication and Radar Coexistence

Cheng Wang; Jianfei Tong; Gaofeng Cui; Xiaoyan Zhao; Weidong Wang

This paper explores spectrum sharing challenges between V2V communication and automotive radar and introduces an interference cancellation algorithm to enhance V2V communication performance.

Signal Processing
Milli-RIO: Ego-Motion Estimation With Low-Cost Millimetre-Wave Radar

Y. Almalioglu; M. Turan; C. X. Lu; N. Trigoni; A. Markham

Introduce Milli-RIO, an MMWave radar-based solution making use of a single-chip low-cost radar and inertial measurement unit sensor to estimate six-degrees-of-freedom ego-motion of a moving radar.

Signal Processing
Clustering and Subsequent Contour and Motion Estimation of Automotive Objects Using a Network of Cooperative Radar Sensors

J. Schlichen-maier; M. Steiner; T. Grebner; C. Waldschmidt

A method for collaborative target list processing of multiple radar sensors simultaneously estimating multiple extended targets is presented and discussed.

Signal Processing
Calibration and Signal Processing of Polarimetric Radar Data in Automotive Applications

F. Weishaupt; J. F. Tilly; N. Appenrodt; J. Dickmann; D. Heberling

This paper demonstrates how to achieve the necessary stability in the scattering information of an automotive multiple input multiple output (MIMO) millimeter wave radar.

Signal Processing
Research On Traffic Information Perception Technology Based On Radar And Video Fusion

Xingyu Zhang; Liping Guo; Weiwei Meng

In this paper, the traffic information perception technology based on the radar and video fusion is investigated, which organically integrates the detection data of millimeter wave radar and visual sensors.

Signal Processing
Automotive radar gridmap representations.

K Werber, Matthias app, Jens Klappstein, Jurgen Dickmann

The first approach utilizes amplitude-based information, while the second employs an occupancy grid-mapping approach with a modified inverse sensor measurement model.

Grid Mapping
Road Scene Understanding by Occupancy Grid Learning from Sparse Radar Clusters using Semantic Segmentation.

L Sless, Gilad Cohen

Employs deep learning techniques to learn the inverse sensor model for occupancy grid mapping from clustered radar data

Grid Mapping
Semi-markov process based localization using radar In dynamic environments.

M Rapp, Markus Hahn, Jurgen Dickmann, Klaus Dietmayer

It presents a robust Monte-Carlo based localization approach that incorporates stochastic analysis of past observations. The model employs a grid-based Markov chain and extends it with a Lévy process to assess reliability and prediction for each grid cell.

Grid Mapping
Semantic segmentation on radar point clouds.

O Schumann, Markus Hahn, Jurgen Dickmann

Unlike previous methods that relied on clustered reflections and manually selected features, this approach eliminates the need for clustering algorithms and manual feature selection.

Grid Mapping
A cognitive perception/action cycle for a notional fighter radar

D. M. Zasada, M. C. Arabadjis, L. D. Tromp

This paper discusses simulating a cognitive perception-action cycle and applying its algorithms to a notional medium PRF fighter radar featuring an adaptive advanced electronically scanned array.

Cognitive Radar
Cognitive radar: a way of the future

S. Haykin

Survey on cogonitive Radar: Three ingredients 1) intelligent signal processing,; 2) feedback from the receiver to the transmitter; and 3) preservation of the information content of radar returns (tracking)

Cognitive Radar
New Algorithms in Cognitive Radar

Huan Zhu, Zhangqin Zhu, Feng Su, Jianzhi Zhang

the key algorithms in intelligent cognitive radar and the effects in improving the radar performance of these algorithms are discussed

Cognitive Radar
Cognitive Waveform Designing Based on Cognitive Radar Theory

Donglin Tan; Junfeng Wang

A novel cognitive waveform designing method is presented for radar target detection based on cognitive radar theory. (to effectively improve the SNR)

Cognitive Radar
Automated Radar Mount-Angle Calibration in Automotive Applications

M. Z. Ikram, A. Ahmad

In this paper, we present a new method for sensor calibration that is easy to execute, is repeatable with minimal supervision, and yields close-toaccurate results.

Vehicle Attitude Estimation
Instantaneous ego-motion estimation using multiple Doppler radars

D. Kellner, M. Barjenbruch, J. Klappstein, J. Dickmann, K. Dietmayer

A robust algorithm using radar sensors to instantly determine the complete 2D motion state of the ego-vehicle. It evaluates the relative motion between at least two Doppler radar sensors and their received stationary reflections (targets).

Vehicle Attitude Estimation
Millimeter-Wave Radar in-the-Loop Testing for Intelligent Vehicles

B.Zhu, Y.Sun, J.Zhao, S. Zhang, P. Zhang, D. Song

1.the millimeter-wave radar in-the-loop (mmRil) testing for intelligent vehicles is proposed in this study. 2.A geometric model of radar target detection and a power attenuation model under bad weather conditions are built to make the simulated target more similar to the real target in terms of its attributes.

Radar Testing
Machine Learning-Based Radar Perception for Autonomous Vehicles Using Full Physics Simulation

Arien P. Sligar

In this paper, an investigation of a machine learning based radar perception algorithm for object detection is implemented, along with a novel, automated workflow for generating large-scale virtual datasets used for training and testing.

Radar Testing
Millimeter wave FMCW radar system simulations including a 3D ray tracing channel simulator

M. Dudek, R. Wahl, D. Kissinger, R. Weigel, G. Fischer

In this paper proposes a millimeter-wave radar system simulation environment for frequency-modulated continuous-wave (FMCW) radar using a 3D ray tracing channel simulator is presented.

Radar Testing
Automotive radar the key technology for autonomous driving: From detection and ranging to environmental understanding

J. Dickmann, J. Klappstein, M. Hahn, N. Appenrodt, H. Bloecher, K. Werber, A. Sailer

An overview on state of the art automotive radar usage is presented and the changing requirements from detection and ranging towards radar based environmental understanding for highly automated and autonomous driving deduced.

Survey
Review of radar classification and RCS characterisation techniques for small UAVs or drones

J. S. Patel, F. Fioranelli, D. Anderson

This review explores radar-based techniques currently utilised in the literature to monitor small unmanned aerial vehicle (UAV) or drones; several challenges have arisen due to their rapid emergence and commercialisation within the mass market.

Survey
Present research activities and future requirements on automotive radar from a car manufacturer´s point of view

J. Dickmann, J. Klappstein, M. Hahn, M. Muntzinger, N. Appenrodt, C. Brenk, A. Sailer

A survey. The paper will provide an overview on state of the art automotive radar usage on the basis of the DAIMLER car platforms, will give an outline on future requirements for highly automated driving and will present recent approaches in radar based environmental perception.

Survey
Machine Learning and Deep Learning Techniques for Colocated MIMO Radars: A Tutorial Overview

A Davoli; G. Guerzoni; G. M. Vitetta

A comprehensive overview of the machine learning and deep learning techniques currently being considered for their use in radar systems is provided. Moreover, some relevant open problems and current trends in this research area are analysed

Survey
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