基于RSS的目标定位算法设计任务书
2020-04-24 11:15:44
1. 毕业设计(论文)的内容和要求
基于mems(微机电系统)的微传感技术和无线联网技术为wsns赋予了广阔的应用前景,使其在军事、航空、反恐、防爆、救灾、环境、医疗、家居、工业、商业等领域发挥了重要作用。
在这些应用中,人们不仅关心多个监测目标的状态,而且关心这些目标的位置,只有获取位置信息后才能采取合理的应对措施。
特别地,传感器的感知数据只有在获得目标位置信息后才具有更高的使用价值。
2. 参考文献
[1]Pivato P, Palopoli L, Petri D. Accuracy of RSS-Based centroid localization algorithms in an indoor environment[J]. IEEE Transactions on Instrumentation Measurement, 2011, 60(10):3451-3460. [2]Tomic S, Beko M, Rui D. 3-D Target localization in wireless sensor network using RSS and AoA measurements[J]. IEEE Transactions on Vehicular Technology, 2016, 99:1-3. [3]倪巍,王宗欣. 基于接收信号强度测量的室内定位算法[J]. 复旦学报(自然科学版), 2004, 43(1):72-76. [4]武晓琳,单志龙,曹树林,等. 基于接收信号强度指示测距的蒙特卡罗盒移动节点定位算法[J]. 计算机应用, 2015, 35(4):916-920. [5] Berg E V D, Friedlander M P. Sparse optimization with least-squares constraints[J]. 2011, 21(4):1201-1229. [6] Chen SS, DonohoDL, Saunders MA. Atomic decomposition by basis pursuit[J]. SIAMJ.Sci. Comput. 1998, 20: 33-61. [7] Lan K C, Wei M Z. A compressibility-based clustering algorithm for hierarchical compressive data gathering[J]. IEEE Sensors Journal, 2017, 17(8): 2550-2562. [8]Pelant J, Tlamsa Z, Benes V, et al. BLE device indoor localization based on RSS fingerprinting mapped by propagation modes[C]//Radioelektronika(RADIOELEKTRONIKA), 2017 27th International Conference. IEEE, 2017: 1-5. [9] Chen F, Valaee S, and Tan Z. Multiple target localization using compressive sensing[C]. IEEE Global Telecommunications Conference (GLOBECOM), Honolulu, HI, USA, 2009: 1-6. [10] Chen W, Yan J, and Zhu W P. Wireless sensor network location algorithm using compressive sensing and multilateral measurements[J]. Journal of Signal Processing, 2014, 30(6): 728-735. [11] Patwari N, Ash J N, Kyperountas S, et al. Locating the nodes: cooperative localization in wireless sensor networks[J]. IEEE Signal Processing Magazine, 2005, 22(4):54-69.
3. 毕业设计(论文)进程安排
第1-3周 收集资料,熟悉课题; 第4-10周 读文献,开始课题学习、研究,上机实验; 第11-14周 论文写作; 第15周 论文整理、定稿并打印; 第16周 论文答辩准备。