TY - GEN
T1 - Potential of GPU-based grid traverse algorithm for lightning geolocation
AU - Qin, Zilong
AU - Cummer, Steven A.
AU - Du, Yaping
AU - Chen, Mingli
AU - Zhu, Baoyou
AU - Lyu, Fanchao
AU - Liu, Feifan
PY - 2019/6
Y1 - 2019/6
N2 - Differing from the traditional Time Difference of Arrival (TDOA) lightning location technique, Grid Traverse Algorithm (GTA) is to build up a series of grid points based on numerical discretion of lightning locations in a network region concerned and then to find the lightning location solution by traversing the grid points. Although GTA has advantages over traditional TOA method in many aspects, it is computationally ineffectiveness. To accelerate the GTA processing speed, we have recently proposed a Graphics Processing Unit (GPU) based GTA parallel computing technique, which is proven to be much faster than the existing CPU based GTA technique. In this paper, we give firstly a briefing of the GPU-GTA technique and then the results of performance test of the technique. The performance test is done by applying the GPU-GTA to a specific lightning location network (LLN) with the Monte Carlo simulation approach. The test results show that GPU-GTA can take about 4.3 seconds, 3.6 seconds and 3.2 seconds to locate 1000 points in 3D at the accuracy of 25 m, 50 m and 100 m respectively. The high performance of the GPU-GTA makes it feasible for a real-time LLN with high accuracy.
AB - Differing from the traditional Time Difference of Arrival (TDOA) lightning location technique, Grid Traverse Algorithm (GTA) is to build up a series of grid points based on numerical discretion of lightning locations in a network region concerned and then to find the lightning location solution by traversing the grid points. Although GTA has advantages over traditional TOA method in many aspects, it is computationally ineffectiveness. To accelerate the GTA processing speed, we have recently proposed a Graphics Processing Unit (GPU) based GTA parallel computing technique, which is proven to be much faster than the existing CPU based GTA technique. In this paper, we give firstly a briefing of the GPU-GTA technique and then the results of performance test of the technique. The performance test is done by applying the GPU-GTA to a specific lightning location network (LLN) with the Monte Carlo simulation approach. The test results show that GPU-GTA can take about 4.3 seconds, 3.6 seconds and 3.2 seconds to locate 1000 points in 3D at the accuracy of 25 m, 50 m and 100 m respectively. The high performance of the GPU-GTA makes it feasible for a real-time LLN with high accuracy.
KW - GPU-based parallel computing technique
KW - Lightning electromagnetic pulse
KW - Lightning source location
KW - Time of arrival technique
UR - http://www.scopus.com/inward/record.url?scp=85072320355&partnerID=8YFLogxK
U2 - 10.1109/APL.2019.8815955
DO - 10.1109/APL.2019.8815955
M3 - Conference article published in proceeding or book
AN - SCOPUS:85072320355
T3 - 2019 11th Asia-Pacific International Conference on Lightning, APL 2019
BT - 2019 11th Asia-Pacific International Conference on Lightning, APL 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th Asia-Pacific International Conference on Lightning, APL 2019
Y2 - 12 June 2019 through 14 June 2019
ER -