Design of airborne target tracking accelerator based on KCF

Yang, Haoran; Yu, Jinxiang; Wang, Shaojun; Peng, Xiyuan

doi:10.1049/joe.2018.9159

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…Shao et al [35] established a velocity correlation flter (VCF) using velocity features and an inertia mechanism (IM). Yang et al [36] embedded the KCF tracker into an unmanned aerial vehicle (UAV) tracking platform. Te KCF tracker maintained high operating speed due to its low time complexity.…”

Section: Introductionmentioning

confidence: 99%

KCF-Based Identification Approach for Vibration Displacement of Double-Column Bents under Various Earthquakes

Cai

XIE

2023

Structural Control and Health Monitoring

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Vibration displacements are one of the most significant indicators in the health monitoring and condition assessment of bridges in the life cycle. The traditional monitoring means, such as contact sensors, have relatively high-cost and limited points for displacement measurement of bridges. This paper proposes a low-cost and non-contact monocular vision system based on the KCF algorithm to accurately and timely identify the vibration displacement of bridges. A conversion method associated with a scale ratio was established to cope with the loss of depth information in images when a monocular camera is used to monitor multiple targets in different depths of the field. A series of shaking table tests on a two-column pier with energy dissipation beams were conducted to verify the feasibility, accuracy, effectiveness, and robustness of the KCF-based identification approach. The results showed that the vibration displacements of the column identified by the monocular vision system based on the KCF algorithm are almost consistent with the measurement results obtained by the laser displacement sensors. The peak displacement discrepancies between both measurement methods are within 6% for all cases with different shaking amplitudes and earthquake waves. The RMSE of the displacement histories between both measurement methods is very low. The corresponding frequency spectra contents identified by the monocular vision system based on the KCF algorithm match well with the measurement counterparts recorded from the laser displacement sensors.

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Section: Introductionmentioning

confidence: 99%

KCF-Based Identification Approach for Vibration Displacement of Double-Column Bents under Various Earthquakes

Cai

XIE

2023

Structural Control and Health Monitoring

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“…Therefore, FPGAs which are proposed as an alternative to DSP-based processors with their parallel processing capability and fast system response, are preferred in applications where the control and estimator algorithms should be performed with low T. In the FPGA-based industrial applications, system generator toolboxes like hardware description language (HDL) coder and Xilinx System Generator which are embedded in Matlab Simulink and require to pay registration charge for licence key are usually used to generate automatically the HDL commands for FPGA hardware synthesis [46]. These tools have excellent performance in generating HDL codes for digital design beside the handwritten HDL code in the manner of time spent [47,48]. However, handwritten HDL coding always stands out in terms of area constraint, power consumption, operating speed, and getting good control performance [5,47,49,50].…”

Section: Introductionmentioning

confidence: 99%

A novel FPGA‐Based Bi input‐reduced order extended Kalman filter for speed‐sensorless direct torque control of induction motor with constant switching frequency controller

İnan

2021

IET Computers & Digital Tech

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This study proposes an FPGA‐based hardware in the loop (HIL) emulator for speed‐sensorless of induction motor (IM) constant switching frequency controller‐based direct torque control (CSFC‐DTC) with a novel bi input‐reduced order extended Kalman filter (BI‐ROEKF). The full precision single floating point numbers in the IEEE 754 standard are used during the implementation of the HIL emulator which contains closed‐loop speed‐sensorless drive system of IM on the Xilinx Virtex XC5VLX‐110T ML506 FPGA board. In this HIL emulator of speed‐sensorless IM drive system, stator stationary axis components of stator flux, rotor mechanical angular speed, load torque, stator and rotor resistances are estimated with the novel BI‐ROEKF which is proposed for the first time in the literature. The proposed BI‐ROEKF is created by applying two different non‐linear and linear system input functions obtained from two different IM models to the single reduced order extended Kalman filter (ROEKF) algorithm. Thus, the order and the computational burden of the EKF are reduced. The HIL emulator of the speed‐sensorless drive system of IM is implemented on FPGA using the advantage of hand‐written VHDL on getting an optimal logical design to reduce the sampling time which directly effects the estimation performance of the model‐based estimator like the novel BI‐ROEKF and hence the control performance of drive system. The estimation performance of the novel BI‐ROEKF is tested with speed‐sensorless CSFC‐DTC IM drive system under different challenging scenarios in HIL emulator. Thus, the control and the implementation performances of digitalised emulator are tested. Finally, the estimation and control performance results and the execution time of the each part of the proposed HIL emulator of the speed‐sensorless BI‐ROEKF‐based CSFC‐DTC of the IM are presented.

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“…Most of these embedded system studies of visual tracking are based on traditional hardware architectures. For example, in [ 22 ], the author utilizes EDMA (enhanced direct memory access) and the caching technique to optimize the Camshift algorithm, which is based on the DSP of TI (Texas Instruments) company, and a frame rate of 3 fps can be realized. Liu W [ 23 ] optimizes the tracking algorithm from a programming perspective based on the DSP of TI company by including an option for setting the compiler optimization and improving the code loop structure, among other changes.…”

Section: Introductionmentioning

confidence: 99%

Study on the Moving Target Tracking Based on Vision DSP

Gong

Wang

et al. 2020

Sensors

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The embedded visual tracking system has higher requirements for real-time performance and system resources, and this is a challenge for visual tracking systems with available hardware resources. The major focus of this study is evaluating the results of hardware optimization methods. These optimization techniques provide efficient utilization based on limited hardware resources. This paper also uses a pragmatic approach to investigate the real-time performance effect by implementing and optimizing a kernel correlation filter (KCF) tracking algorithm based on a vision digital signal processor (vision DSP). We examine and analyze the impact factors of the tracking system, which include DP (data parallelism), IP (instruction parallelism), and the characteristics of parallel processing of the DSP core and iDMA (integrated direct memory access). Moreover, we utilize a time-sharing strategy to increase the system runtime speed. These research results are also applicable to other machine vision algorithms. In addition, we introduced a scale filter to overcome the disadvantages of KCF for scale transformation. The experimental results demonstrate that the use of system resources and real-time tracking speed also satisfies the expected requirements, and the tracking algorithm with a scale filter can realize almost the same accuracy as the DSST (discriminative scale space tracking) algorithm under a vision DSP environment.

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Design of airborne target tracking accelerator based on KCF

Cited by 6 publications

References 11 publications

KCF-Based Identification Approach for Vibration Displacement of Double-Column Bents under Various Earthquakes

KCF-Based Identification Approach for Vibration Displacement of Double-Column Bents under Various Earthquakes

A novel FPGA‐Based Bi input‐reduced order extended Kalman filter for speed‐sensorless direct torque control of induction motor with constant switching frequency controller

Study on the Moving Target Tracking Based on Vision DSP

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