Automotive radar target tracking by Kalman filtering
Automotive radars have been introduced successfully into the consumer market with sensors in the 24- and 77-GHz domain [1]. In order to increase traffic safety, an application for detecting and tracking Vulnerable Road Users (VRU) and vehicles in front of the car is currently under development. By using a single 24-GHz radar sensor, target parameters like range, radial velocity and azimuth angle are measured even in multiple target scenarios. This paper describes the current implementation progress of a signal processing scheme for target tracking by Kalman filtering and presents tracking results using real measurement data. The work is developed under the FP7 EC funded project ARTRAC [2].
Two-stage pedestrian classification in automotive radar systems
Road and city traffic is dangerous for all car drivers and especially for pedestrians. Latest accident statistics [1] show that in 25% of all accidents pedestrians are involved. It is therefore important to protect especially those vulnerable traffic participants, e.g. by acoustic alarm signals or outside airbags, in case of an unavoidable accident. 24 GHz radar sensors with their all-weather capability are already in use in vehicles, and have great advantages compared with other automotive sensor systems. It has been described in [2], how the Doppler spectrum and the range profile are analyzed in a target recognition system for pedestrian detection. To increase the probability of correct classification, additional signal features have to be used. Also, a very fast target recognition system is required to respond and react quickly in dangerous situations. This paper is focused on a two-stage target classification system. Initially, the Doppler spectrum and range profile are extracted from the radar echo signal and applied in the recognition system. In a second step, additional features are calculated from the tracker which are fed back to the target recognition system to improve the system performance and to increase the probability of correct classification.
COMBINATION OF LFMCW AND FSK MODULATION PRINCIPLES FOR AUTOMOTIVE RADAR SYSTEMS Symposium Topic: Automotive Radar
High performance automotive radar systems are currently under development for various applications. Comfort systems like Adaptive Cruise Control (ACC) are already available on the market as 77 GHz radars. Target range and velocity are measured simultaneously with high resolution and accuracy even in multi-target situations but the measurement and processing time to detect the relevant object is approximately 100 ms. Future developments will be more concentrated on safety applications like Collision Avoidance (CA) or Autonomous Driving (AD). In this case the requirements for reliability (extreme low false alarm rate) and reaction time (extreme short delay) are much higher compared with ACC systems.