Raw ADC Data of 77GHz MMWave radar for Automotive Object Detection

In this dataset, we provided the raw analog-to-digital-converter (ADC) data of a 77GHz mmwave radar for the automotive object detection scenario. The overall dataset contains approximately 19800 frames of radar data as well as synchronized camera images and labels. For each radar frame, its raw data has 4 dimension: samples (fast time), chirps (slow time), transmitters, receivers. The experiment radar was assembled from the TI AWR 1843 board, with 2 horizontal transmit antennas and 4 receive antennas. With time-division multiplexing on all transmitters, it can form a 1D-MIMO virtual array with 8 elements. The data collection was done on the campus, road, and parking lot during the daytime, focusing on capturing the data for six main objects: pedestrian, cyclist, car, motorbike, bus, and truck. The collected objects can be either moving (mostly) or static. A single data collection run consisted of multiple objects listed above moving or being static at an average speed for 30 seconds in front of the testbed. More information in terms of dataset structure, format, tools, and radar configuration was described in README documentation.

本数据集收录了针对77GHz毫米波雷达在汽车目标检测场景下的原始模拟-数字转换器（ADC）数据。该数据集总体包含约19800帧雷达数据以及同步的摄像头图像和标签。对于每一帧雷达图像，其原始数据具有四个维度：样本（快速时间）、脉冲（慢速时间）、发射器、接收器。实验中所用的雷达由TI AWR 1843板组装而成，配备2个水平发射天线和4个接收天线。通过所有发射器的时分复用，可以形成一个包含8个元素的1D-MIMO虚拟阵列。数据采集在校园、道路和停车场进行，时间选择在白天，主要针对以下六种主要目标的雷达数据进行捕捉：行人、自行车、汽车、摩托车、公交车和卡车。收集的对象可以是移动的（主要）或静止的。单一的数据采集过程包括上述多个对象在测试平台前以平均速度持续30秒的移动或静止。关于数据集结构、格式、工具和雷达配置的更多信息，请参阅README文档。

搜集汇总

背景与挑战

背景概述

该数据集提供了77GHz毫米波雷达的原始ADC数据，专为汽车目标检测场景设计，包含约19800帧雷达数据以及同步的相机图像和标签，数据格式为MAT、JPG和CSV。数据集针对行人、骑行者、汽车等六类交通对象，在校园、道路和停车场等环境中收集，支持移动和静态对象检测，并基于TI AWR 1843板实现1D-MIMO虚拟阵列，适用于信号处理和机器学习研究。