Trade-Off Exploration for Target Tracking Application in a Customized Multiprocessor Architecture
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Research Article Trade-Off Exploration for Target Tracking Application in a Customized Multiprocessor Architecture Jehangir Khan,1 Smail Niar,1 Mazen A. R. Saghir,2 Yassin El-Hillali,1 and Atika Rivenq-Menhaj1 1 Universit´ e
de Valenciennes et du Hainaut-Cambr´esis, ISTV2 - Le Mont Houy, 59313 Valenciennes Cedex 9, France of Electrical and Computer Engineering, Texas A&M University at Qatar, 23874 Doha, Qatar
2 Department
Correspondence should be addressed to Smail Niar, [email protected] Received 16 March 2009; Revised 30 July 2009; Accepted 19 November 2009 Recommended by Markus Rupp This paper presents the design of an FPGA-based multiprocessor-system-on-chip (MPSoC) architecture optimized for Multiple Target Tracking (MTT) in automotive applications. An MTT system uses an automotive radar to track the speed and relative position of all the vehicles (targets) within its field of view. As the number of targets increases, the computational needs of the MTT system also increase making it difficult for a single processor to handle it alone. Our implementation distributes the computational load among multiple soft processor cores optimized for executing specific computational tasks. The paper explains how we designed and profiled the MTT application to partition it among different processors. It also explains how we applied different optimizations to customize the individual processor cores to their assigned tasks and to assess their impact on performance and FPGA resource utilization. The result is a complete MTT application running on an optimized MPSoC architecture that fits in a contemporary medium-sized FPGA and that meets the application’s real-time constraints. Copyright © 2009 Jehangir Khan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction Technological progress has certainly influenced every aspect of our lives and the vehicles we drive today are no exception. Fuel economy, interior comfort, and entertainment features of these vehicles draw ample attention but the most important objective is to aid the driver in avoiding accidents. Road accidents are primarily caused by misjudgment of a delicate situation by the driver. The main reason behind the driver’s inability to judge a potentially dangerous situation correctly is the mental and physical fatigue due the stressful driving conditions. In cases where visibility is low due to poor weather or due to night-time driving, the stress on the driver increases even further. An automatic early warning and collision avoidance system onboard a vehicle can greatly reduce the pressure on the driver. In the literature, such systems are called Driver Assistance Systems (DASs). DASs not only automatize safety mechanisms in a vehicle but also help drivers take correct and quick decisions in delicate situations. These systems provide the driver with a realistic assessment of
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