Dynamic programming network for point target detection
Abstract To improve the efficiency of the dim point target detection based on dynamic programming (DP), this paper proposes a multi-frame target detection method based on a DP ring network (DPRN). In the proposed method, first, the target trajectory is approximated using the piecewise linear functio...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-06-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13634-023-01038-7 |
| _version_ | 1797789474130755584 |
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| author | Jingneng Fu Hongyan Wei |
| author_facet | Jingneng Fu Hongyan Wei |
| author_sort | Jingneng Fu |
| collection | DOAJ |
| description | Abstract To improve the efficiency of the dim point target detection based on dynamic programming (DP), this paper proposes a multi-frame target detection method based on a DP ring network (DPRN). In the proposed method, first, the target trajectory is approximated using the piecewise linear function. The velocity space partition DP (VSP-DP) is used to accumulate the merit functions of a target on each piecewise linear trajectory segment to avoid the merit function diffusion in different velocity spaces. In addition, the velocity space matching DP (VSM-DP) is employed to realize the state transition of a target between adjacent piecewise linear trajectory segments. Then, the VSP-DP and VSM-DP are used to construct a DP network (DPN). Second, to suppress the merit function diffusion further, the sequential and reverse DPNs are connected in a head-to-tail manner to form a DPRN, and the merit function of the DPRN is obtained by averaging the merit functions of the sequential and reverse DPNs. Finally, the target trajectory is obtained by tracking the extreme points of the merit functions of the DPRN. The simulation and analysis results show that the proposed DPRN combines the advantages of high detection probability of the high-order DP and high execution efficiency of the first-order DP. The proposed DPRN is suitable for radars and infrared searching and tracking systems. |
| first_indexed | 2024-03-13T01:51:10Z |
| format | Article |
| id | doaj.art-125ed2b6b2f94eacabcae39976350efb |
| institution | Directory Open Access Journal |
| issn | 1687-6180 |
| language | English |
| last_indexed | 2024-03-13T01:51:10Z |
| publishDate | 2023-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-125ed2b6b2f94eacabcae39976350efb2023-07-02T11:29:34ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802023-06-012023111810.1186/s13634-023-01038-7Dynamic programming network for point target detectionJingneng Fu0Hongyan Wei1Institute of Optics and Electronics, Chinese Academy of SciencesInstitute of Optics and Electronics, Chinese Academy of SciencesAbstract To improve the efficiency of the dim point target detection based on dynamic programming (DP), this paper proposes a multi-frame target detection method based on a DP ring network (DPRN). In the proposed method, first, the target trajectory is approximated using the piecewise linear function. The velocity space partition DP (VSP-DP) is used to accumulate the merit functions of a target on each piecewise linear trajectory segment to avoid the merit function diffusion in different velocity spaces. In addition, the velocity space matching DP (VSM-DP) is employed to realize the state transition of a target between adjacent piecewise linear trajectory segments. Then, the VSP-DP and VSM-DP are used to construct a DP network (DPN). Second, to suppress the merit function diffusion further, the sequential and reverse DPNs are connected in a head-to-tail manner to form a DPRN, and the merit function of the DPRN is obtained by averaging the merit functions of the sequential and reverse DPNs. Finally, the target trajectory is obtained by tracking the extreme points of the merit functions of the DPRN. The simulation and analysis results show that the proposed DPRN combines the advantages of high detection probability of the high-order DP and high execution efficiency of the first-order DP. The proposed DPRN is suitable for radars and infrared searching and tracking systems.https://doi.org/10.1186/s13634-023-01038-7Point target detectionDynamic programmingDynamic programming ringDynamic programming networkMerit function diffusion suppression |
| spellingShingle | Jingneng Fu Hongyan Wei Dynamic programming network for point target detection EURASIP Journal on Advances in Signal Processing Point target detection Dynamic programming Dynamic programming ring Dynamic programming network Merit function diffusion suppression |
| title | Dynamic programming network for point target detection |
| title_full | Dynamic programming network for point target detection |
| title_fullStr | Dynamic programming network for point target detection |
| title_full_unstemmed | Dynamic programming network for point target detection |
| title_short | Dynamic programming network for point target detection |
| title_sort | dynamic programming network for point target detection |
| topic | Point target detection Dynamic programming Dynamic programming ring Dynamic programming network Merit function diffusion suppression |
| url | https://doi.org/10.1186/s13634-023-01038-7 |
| work_keys_str_mv | AT jingnengfu dynamicprogrammingnetworkforpointtargetdetection AT hongyanwei dynamicprogrammingnetworkforpointtargetdetection |