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αβ 필터 및 NNPDA 알고리즘을 이용한 차량용 레이더 표적 추적 시스템 설계

αβ 필터 및 NNPDA 알고리즘을 이용한 차량용 레이더 표적 추적 시스템 설계
Alternative Title
An Automotive Radar Target Tracking System Design using αβ Filter and NNPDA Algorithm
DGIST Authors
Issued Date
Automotive Radar Systems are currently under development for various applications to increase accuracy and reliability. The target tracking is most important in single or multiple target environments for accuracy. The tracking algorithm provides smoothed and predicted data for target position and velocity(Doppler). To this end, the fixed gain filter( filter, filter) and dynamic filter(Kalman filter, Singer-Kalman filter, etc) are commonly used. Gating is used to decide whether an observation is assigned to an existing track or new track. Gating algorithms are normally based on computing a statistical error distance between an observation and prediction. The data association takes the observation-to-track pairings that satisfied gating and determines which observation-to-track assignment will actually be made. For data association, NNPDA(Nearest Neighbor Probabilistic Data Association) algorithm is proposed. In this paper, we designed a target tracking system developed for an Automotive Radar System. We show the experimental results of the 77GHz FMCW radar sensor on the roads. Four tracking algorithms( filter, filter, 2nd order Kalman filter, Singer-Kalman filter) have been compared and analyzed to evaluate the performance in test scenario.
Related Researcher
  • 현유진 Hyun, Eugin 미래자동차연구부
  • Research Interests Radar system; Radar signal processing; Automotive radar; Surveillance radar; Commercial radar; Defence radar
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Appears in Collections:
Division of Intelligent Robotics 1. Journal Articles
Division of Automotive Technology Advanced Radar Tech. Lab 1. Journal Articles
Division of Automotive Technology 1. Journal Articles


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