Processing latency effects on resource management in rotating AESA radar

Wielgo, Maciej; Misiurewicz, Jacek; Radecki, Krzysztof

doi:10.23919/irs.2017.8008154

Cited by 1 publication

(3 citation statements)

References 3 publications

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“…However, there is an error according to the object vehicle's velocity due to the radar's latency (the results of the analysis of the experimental data are shown in Section 4). This is caused by the object tracking algorithm of commercial radars [14,29]. This is a problem for anyone designing high-level applications for radar.…”

Section: Data-driven Radar Accuracy Modelingmentioning

confidence: 99%

“…As stated above, by applying a filter without an additional sensor, accurate tracking is possible without increasing the cost. However, radar latency (processing delay) increases with the use of a filter [16,29,30]. This latency increases further depending on the tracking algorithm used (e.g., point cloud clustering, segmentation, single sensor tracking, multilateration, classification, and filtering) in vehicle applications [7,14,31,32].…”

Section: Introductionmentioning

confidence: 99%

“…This latency increases further depending on the tracking algorithm used (e.g., point cloud clustering, segmentation, single sensor tracking, multilateration, classification, and filtering) in vehicle applications [7,14,31,32]. In this regard, the radar sensor was evaluated for the effect of processing latency on the efficiency of detecting, acquiring, and tracking a target [29]. In [33], the authors noted that it is important for delays in the measurement (i.e., the time elapsed since a physical event occurs until it is output to the application) and accurate data on the position of other vehicles in future driver assistance systems.…”

Section: Introductionmentioning

confidence: 99%

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Data-Driven Object Vehicle Estimation by Radar Accuracy Modeling with Weighted Interpolation

Choi

Yang

Chung

2021

Sensors

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For accurate object vehicle estimation using radar, there are two fundamental problems: measurement uncertainties in calculating an object’s position with a virtual polygon box and latency due to commercial radar tracking algorithms. We present a data-driven object vehicle estimation scheme to solve measurement uncertainty and latency problems in radar systems. A radar accuracy model and latency coordination are proposed to reduce the tracking error. We first design data-driven radar accuracy models to improve the accuracy of estimation determined by the object vehicle’s position. The proposed model solves the measurement uncertainty problem within a feasible set for error covariance. The latency coordination is developed by analyzing the position error according to the relative velocity. The position error by latency is stored in a feasible set for relative velocity, and the solution is calculated from the given relative velocity. Removing the measurement uncertainty and latency of the radar system allows for a weighted interpolation to be applied to estimate the position of the object vehicle. Our method is tested by a scenario-based estimation experiment to validate the usefulness of the proposed data-driven object vehicle estimation scheme. We confirm that the proposed estimation method produces improved performance over the conventional radar estimation and previous methods.

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Section: Data-driven Radar Accuracy Modelingmentioning

confidence: 99%