Study on track and detect algorithm in radar networking based on gmphd
Xitong Fangzhen Xuebao / Journal of System Simulation, ISSN: 1004-731X, Vol: 28, Issue: 11, Page: 2804-2812
2016
- 41Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage41
- Downloads41
Article Description
The states and number of WSNR multi-target are tracked accurately by Gaussian mixture probability hypothesis density algorithm (GMPHDA) application. But tracking result is random set of target states, it doesn't correspond one to one with real targets. And the complete algorithm about corresponding has not been proposed. To get target tracks corresponding with real targets, a suite of algorithm about identifying target tracks is proposed, called track identification algorithm, which contains track distinction, continuance, newborn and restoration. The track identification algorithm improves track and detect algorithm in multi-radar networking. Simulation results show that WSNR multi-target is tracked in multi-radar networking, which gets target tracks corresponding one to one with real targets by the proposed identification algorithm.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85012964781&origin=inward; http://dx.doi.org/10.16182/j.issn1004731x.joss.201611023; https://dc-china-simulation.researchcommons.org/journal/vol28/iss11/23; https://dc-china-simulation.researchcommons.org/cgi/viewcontent.cgi?article=3302&context=journal; https://dx.doi.org/10.16182/j.issn1004731x.joss.201611023; https://www.chndoi.org/Resolution/Handler?doi=10.16182/j.issn1004731x.joss.201611023; http://sciencechina.cn/gw.jsp?action=cited_outline.jsp&type=1&id=5846369&internal_id=5846369&from=elsevier
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know