# Joint Azimuth, Elevation and Delay Estimation for Single Base Station Localization in 3D IIoT +
## 5 Conclusions  
In this paper, we propose the J-MT localization algorithm for the IIoT, aiming to address the challenges of indoor positioning using a single BS. The proposed method leverages the benefits of MUSIC-based JAEDE to effectively estimate the angle of azimuth, elevation, and time delay of the target. Moreover, the proposed approach eliminates the grid constraints that arise from the grid peak searching of conventional MUSIC-based methods, employing the Taylor-series method with a notable 99% reduction in computational cost compared to the conventional two-step coarse-find grid searching MUSIC method. This advancement not only enhances accuracy but also improves the efficiency of the overall localization process. The comprehensive numerical results obtained through simulations have demonstrated the superiority of our proposed algorithm across various SNR conditions. It consistently outperforms other existing methods, including both separate angle and delay estimation, and two-step joint MUSIC localization algorithms.  
Although the J-MT algorithm is originally proposed for indoor IIoT scenarios, it can also serve as a valuable inspiration for outdoor non-terrestrial network (NTN) applications with appropriate enhancements in both the antenna array and the algorithm design. In NTN scenarios, the longer distances between the airborne BS and the target introduce new challenges that need to be addressed. Firstly, the antenna array design must be improved to achieve higher angular sensitivity, while also considering compact size and low energy consumption. This is necessary to ensure accurate localization performance over extended distances. Secondly, the mobility of the BS, such as unmanned aerial vehicles (UAVs), presents additional obstacles that must be overcome. These include addressing link robustness, handover mechanisms, and potential interferences. By incorporating these improvements, the J-MT algorithm can be effectively adapted for NTN environments, enabling accurate localization even over large outdoor areas.  
Conceptualization, Z.L. and X.Z.; methodology, Z.L.; software, Z.L.; validation, Z.L.; formal analysis, Z.L.; investigation, Z.L.; resources, Z.L.; data curation, Z.L.; writing--original draft preparation, Z.L.; writing--review and editing, Z.L. and X.Z.; visualization, Z.L.; supervision, X.Z.; project administration, X.Z.; funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the National Natural Science Foundation of China under Grant 62171161; in part by the Guangdong Provincial Science and Technology Program under Grant 2022A0505050022; in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2022B1515120018; in part by the Shenzhen Science and Technology Program under Grants ZDSYS20210623091808025, KGDTD20190929172545139 and GXWD 20220817133854003; in part by the HIT-HKUST Joint Laboratory of Wireless Deterministic Networks.  
Not applicable.  
Data Availability StatementData can be obtained from the corresponding author upon reasonable request.  
The authors declare no conflict of interest.