A novel passive location algorithm based on neural networks

Author(s):  
Luo Zheng ◽  
Donghua Liu ◽  
Yu Fei
Author(s):  
В.Н. Юдин ◽  
А.М. Волков

Рассмотрены варианты повышения точности угломерной пассивной локации источников излучения с использованием одиночного авиационного носителя и алгоритма местоопределения на основе метода наименьших квадратов. Оценены достижимые уровни ошибок локации применительно к различным условиям ведения воздушной разведки источников излучения. Options for improving the accuracy of the goniometric passive location of radiation sources using a single aircraft carrier and location algorithm based on the least square method are considered.The achievable levels of location errors were assessed for different conditions of aerial reconnaissance of radiation sources.


2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Xiaojun Yang ◽  
Gang Liu ◽  
Jinku Guo ◽  
Hongqiao Wang ◽  
Bing He

With the advantages such as high security and far responding distance, the passive location has a broad application in military and civil domains such as radar and aerospace. However, most of the current passive location methods are based on the framework of the probability theory and cannot be used to deal with fuzzy uncertainty in the passive location systems. Though the fuzzy Kalman filter can be used in the uncertainty systems, it could not deal with the abrupt change of state like the maneuvering target which will lead to the filter divergence. Therefore, in order to track the maneuvering target in the fuzzy passive system, we proposed a robust fuzzy extended Kalman filter based on the orthogonality principle and the fuzzy filter in the paper. Conclusion can be made based on the simulation result that this new approach is more precise and more robust than the fuzzy filter.


2012 ◽  
Vol 462 ◽  
pp. 550-555
Author(s):  
Jie Zhao

An applicable passive location algorithm of target based on single fixed-site illuminator of opportunity is introduced in this paper. The azimuth can be acquired using DBF (digital beam formation) technique and angle-measuring via amplitude comparison. Based on Time Difference of Arrival (TDOA), the distance between the target and the radar station is achievable. Finally, the accuracy of location is analyzed, and the computer simulation results are presented.


2007 ◽  
Author(s):  
En-ke Li ◽  
Shi-min Yin ◽  
Shang-qian Liu ◽  
Xiao-ning Fu ◽  
Da-bao Wang ◽  
...  

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1558 ◽  
Author(s):  
Yao Zhang ◽  
Zhongliang Deng ◽  
Yuhui Gao

Location technology is playing an increasingly important role in urban life. Various active and passive wireless positioning technologies for mobile terminals have attracted research attention. However, positioning signals experience serious interference in high-density residential areas or in the interior of large buildings. The main type of interference is that caused by non-line-of-sight (NLOS) propagation. In this paper, we present a new method for optimizing the angle of arrival (AOA) measurement to obtain high accuracy location results based on proximal policy optimization (PPO). PPO is a new family of policy gradient methods for reinforcement learning, which can be used to adjust the sampling data under different environments using stochastic gradient ascent. Therefore, PPO can correct the NLOS propagation errors to produce a clear AOA measurement data set without building an offline fingerprinting database. Then, we used the least square method to calculate the location. The simulation result shows that the AOA passive location algorithm based on PPO produced more accurate location information.


2014 ◽  
Vol 950 ◽  
pp. 196-200
Author(s):  
Hua Wei Bai ◽  
Yu Wen Wang ◽  
Yu Jiang

The multi station time difference sequence of arrival method is a kind of passive location method for pulse radiation source. It takes the advantage of mass time difference information obtained in a very short time to locate the radiation source. This paper models the time difference sequence of arrival process and estimates the time difference according to the characteristic of the time difference sequence. The simulation results show that, the localization after time sequence estimation algorithm can achieve higher positioning accuracy.


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