# Object Detection and 3D Estimation via an FMCW Radar Using a Fully Convolutional Network

arXiv: https://arxiv.org/abs/1902.05394 · HTML: https://mlsanity.com/paper/1902.05394/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Feb 2019.

## Built on by (most cited first, 17 of 17)

- [Raw High-Definition Radar for Multi-Task Learning](https://mlsanity.com/paper/2112.10646/) (2021)
- [Multi-View Radar Semantic Segmentation](https://mlsanity.com/paper/2103.16214/) (2021)
- [RadarOcc: Robust 3D Occupancy Prediction with 4D Imaging Radar](https://mlsanity.com/paper/2405.14014/) (2024)
- [Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion](https://mlsanity.com/paper/2307.16532/) (2023)
- [RadSimReal: Bridging the Gap Between Synthetic and Real Data in Radar Object Detection With Simulation](https://mlsanity.com/paper/2404.18150/) (2024)
- [TransRadar: Adaptive-Directional Transformer for Real-Time Multi-View Radar Semantic Segmentation](https://mlsanity.com/paper/2310.02260/) (2023)
- [Label-Aware Ranked Loss for robust People Counting using Automotive in-cabin Radar](https://mlsanity.com/paper/2110.05876/) (2021)
- [DoppDrive: Doppler-Driven Temporal Aggregation for Improved Radar Object Detection](https://mlsanity.com/paper/2508.12330/) (2025)
- [SparseRadNet: Sparse Perception Neural Network on Subsampled Radar Data](https://mlsanity.com/paper/2406.10600/) (2024)
- [Radar Image Reconstruction from Raw ADC Data using Parametric Variational Autoencoder with Domain Adaptation](https://mlsanity.com/paper/2207.06379/) (2022)
- [BoostRad: Enhancing Object Detection by Boosting Radar Reflections](https://mlsanity.com/paper/2404.17861/) (2024)
- [Teacher-Student Knowledge Distillation for Radar Perception on Embedded Accelerators](https://mlsanity.com/paper/2303.07586/) (2023)
- [A Resource Efficient Fusion Network for Object Detection in Bird's-Eye View using Camera and Raw Radar Data](https://mlsanity.com/paper/2411.13311/) (2024)
- [mRadNet: A Compact Radar Object Detector with MetaFormer](https://mlsanity.com/paper/2509.16223/) (2025)
- [RadarXFormer: Robust Object Detection via Cross-Dimension Fusion of 4D Radar Spectra and Images for Autonomous Driving](https://mlsanity.com/paper/2603.14822/) (2026)
- [REFNet++: Multi-Task Efficient Fusion of Camera and Radar Sensor Data in Bird's-Eye Polar View](https://mlsanity.com/paper/2605.11824/) (2026)
- [Learning Structurally Consistent Representations for Multi-View Radar Semantic Segmentation](https://mlsanity.com/paper/2606.31609/) (2026)

## Abstract (arXiv)

This paper considers object detection and 3D estimation using an FMCW radar. The state-of-the-art deep learning framework is employed instead of using traditional signal processing. In preparing the radar training data, the ground truth of an object orientation in 3D space is provided by conducting image analysis, of which the images are obtained through a coupled camera to the radar device. To ensure successful training of a fully convolutional network (FCN), we propose a normalization method, which is found to be essential to be applied to the radar signal before feeding into the neural network. The system after proper training is able to first detect the presence of an object in an environment. If it does, the system then further produces an estimation of its 3D position. Experimental results show that the proposed system can be successfully trained and employed for detecting a car and further estimating its 3D position in a noisy environment.