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What is WaveFarer?

WaveFarer is a sophisticated radar simulation platform that proficiently replicates multipath effects and scattering phenomena from adjacent structures and vehicles, along with essential atmospheric influences for frequencies that may surpass 100 GHz. Its wide-ranging applications include modeling automotive driving scenarios, improving indoor sensor performance, and scrutinizing far-field radar cross sections (RCS). The functionalities of WaveFarer enable swift and accurate assessments of situations where radars operate in close proximity to different structures, targets, and environmental characteristics. Specifically designed for radar system simulation, WaveFarer assists in determining the best positioning of automotive radar sensors and analyzing target returns within virtual driving settings. Moreover, it offers critical insights for surveillance radar applications by evaluating the RCS of various targets and examining how different materials affect measurement results, thereby ensuring a thorough comprehension of radar interactions across diverse situations. By leveraging its extensive capabilities, WaveFarer has established itself as an indispensable resource for radar analysis and simulation in numerous fields, making it a key player in elevating the understanding of radar technology.

What is NVIDIA DRIVE Map?

NVIDIA DRIVE® Map is a sophisticated mapping solution specifically designed to bolster vehicle autonomy while prioritizing safety. It combines accurate ground truth mapping with the nimbleness and extensiveness of AI-powered fleet-generated mapping, yielding impressive outcomes. The platform incorporates four unique localization layers—camera, lidar, radar, and GNSS—offering essential redundancy and adaptability for advanced AI-driven systems. Emphasizing unparalleled accuracy, the ground truth map engine creates DRIVE Maps by synthesizing data from various sensors, such as cameras, radars, lidars, and differential GNSS/IMU, all collected via NVIDIA DRIVE Hyperion data collection vehicles. It achieves remarkable precision of under 5 cm, especially in high autonomy contexts (L3/L4), in settings like urban landscapes and highways. Tailored for swift performance and global compatibility, DRIVE Map takes advantage of both ground truth and fleet-generated data, representing the collective intelligence of millions of vehicles on the road. This cutting-edge methodology not only improves mapping accuracy but also plays a vital role in advancing the future of autonomous driving technology, paving the way for safer roadways and smarter transport systems.

Media

Media

Integrations Supported

Baidu
NVIDIA DRIVE
Red Hat Enterprise Linux
Simulink

Integrations Supported

Baidu
NVIDIA DRIVE
Red Hat Enterprise Linux
Simulink

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Remcom

Date Founded

1994

Company Location

United States

Company Website

www.remcom.com/wavefarer-automotive-radar-software

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/self-driving-cars/hd-mapping/

Categories and Features

Simulation

1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling

Categories and Features

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