International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
•
Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
Home
Research Paper
Submit Research Paper
Publication Guidelines
Publication Charges
Upload Documents
Track Status / Pay Fees / Download Publication Certi.
Editors & Reviewers
View All
Join as a Reviewer
Reviewer Referral Program
Get Membership Certificate
Current Issue
Publication Archive
Conference
Publishing Conf. with IJFMR
Upcoming Conference(s) ↓
WSMCDD-2025
GSMCDD-2025
Conferences Published ↓
RBS:RH-COVID-19 (2023)
ICMRS'23
PIPRDA-2023
Contact Us
Plagiarism is checked by the leading plagiarism checker
Call for Paper
Volume 6 Issue 6
November-December 2024
Indexing Partners
Radar Powered Perception: Multiple Approaches for Vehicle Classification
Author(s) | Deepak Kumar Misra, Brijesh Jha, Shyam Raman |
---|---|
Country | India |
Abstract | The proliferation of Advanced Driver-Assistance Systems (ADAS) and autonomous vehicles demands robust and reliable techniques for vehicle detection and classification. This paper investigates the potential of automotive radar systems for this critical task, focusing on classifying vehicles into three distinct categories (bus/truck, car/sedan/SUV, bike/bicycle). We explore multiple approaches that leverages rich set of features extracted from radar measurements. These features include target size, point density, and other signature characteristics derived from the radar return signal. By analyzing these features, we explain multiple approach aims to achieve vehicle classification. The effectiveness of the proposed method is evaluated using real-world data, with a particular focus on demonstrating its suitability for real-time applications in ADAS. The paper delves into the critical trade-offs that exist between classification accuracy, computational complexity, and inherent limitations of automotive radar sensors. We discuss the impact of sparse data, such as low point cloud data on classification accuracy. Additionally, we discuss on potential mitigation strategies to ensure reliability in challenging scenarios. Finally, the paper concludes by outlining potential future directions for enhancing vehicle classification using automotive radar systems. These advancements will pave the way for the development of more robust and reliable ADAS and autonomous vehicles, ultimately contributing to improved safety on our roads. |
Keywords | Automotive Radar, Vehicle Detection, Vehicle Classification, ADAS, Autonomous Vehicles, Point Cloud Data, Machine Learning |
Field | Engineering |
Published In | Volume 6, Issue 4, July-August 2024 |
Published On | 2024-08-24 |
Cite This | Radar Powered Perception: Multiple Approaches for Vehicle Classification - Deepak Kumar Misra, Brijesh Jha, Shyam Raman - IJFMR Volume 6, Issue 4, July-August 2024. DOI 10.36948/ijfmr.2024.v06i04.26482 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i04.26482 |
Short DOI | https://doi.org/gt8g4w |
Share this
E-ISSN 2582-2160
doi
CrossRef DOI is assigned to each research paper published in our journal.
IJFMR DOI prefix is
10.36948/ijfmr
Downloads
All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.