# Detection and Tracking of Weak Exoatmospheric Target with Elliptical Hough Transform
## 6 Conclusions  
When tracking low observable targets in the presence of clutter, more challenges will occur. The TBD is a quite effective scheme to deal with low observable targets, as it exchanges the time for obtaining better SNR according to some accumulation metric. In this paper, still within the TBD framework, we present a new Hough detector, i.e., an elliptical Hough transform (EHT) detector, to detect and track weak exoatmospheric targets in the presence of heavy clutter. Both simulations and field data verify the validity of the algorithm. The advantage of the new algorithm lies in that it is specifically designed for exoatmospheric targets; hence, it indeed has the effect of integrating detection, tracking, and even prediction functions. Nonetheless, for multiple target detection, there are still some issues. One problem is that the number of k-means clustering centers still needs to be adjusted by experience. Another issue is that the secondary threshold also has an impact on the multi-target detection performance, especially in the presence of both large and small targets. All these problems need further investigation.  
This method can also be extended to other situations. For instance, multisensor integration, data fusion, polarizations, and Doppler measurements can also be added to the approach to improve performance. Furthermore, in addition to using geometrical information of elliptical orbit, other motional information can also be used to design a TBD algorithm to detect an exoatmospheric target. For instance, many exoatmospheric targets have conservation characteristics (conservation laws of mechanical energy and moment of momentum); thus, a simple linear Hough transform detector may be used to detect a physically existent target and discriminate between false targets (e.g., active decoys, which are physically non-existent). The previous work has gained some interesting results concerning joint tracking and discrimination [49; 50; 51]; future work will be focused on TBD processing in joint detection and tracking and discrimination of weak exoatmospheric targets in clutter and jamming environments. This will be an intellectually motivating field and needs further investigation.  
Figure 19: Detection and tracking results of EHT with real data, with the primary threshold \(\eta=2.3026\) and secondary threshold \(\eta^{\mathrm{Hough}}=10\). (**a**) in the THIS-CS. (**b**) in the ENU-CS.  
**Author Contributions:** Conceptualization, B.R.; methodology, B.R.; software, B.R.; validation, B.R., Y.Z. and Y.N.; formal analysis, Y.Z.; investigation, B.R.; resources, B.R.; data curation, B.R.; writing--original draft preparation, B.R.; writing--review and editing, Y.Z.; visualization, B.R.; supervision, Y.N.; project administration, Y.N.; funding acquisition, B.R. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was partially funded by Shenzhen Science and Technology Program under Grant KQTD20190929172704911.  
**Institutional Review Board Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** The authors would like to thank the editor and anonymous reviewers for processing our manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.