Signal analysis at the phase discriminator output of the phase direction finder circuit with the frequency substitution

Author(s):  
Ilya D. Zolotarev ◽  
Vladimir A. Berezovskiy ◽  
Denis D. Privalov
2012 ◽  
Vol 55 (9) ◽  
pp. 1093-1095
Author(s):  
E. S. Bespalov ◽  
A. S. Golovnenkova ◽  
M. A. Poletkov

2021 ◽  
Vol 24 (1) ◽  
pp. 7-15
Author(s):  
G. G. Porubov ◽  
◽  
V. P. Denisov ◽  

The algorithm to calculate the azimuth and the elevation angle on the source of radio emission in the topocentric system of coordinates is suggested according to the measurements done by the phase direction finder located on board a mobile object. The position of an aerial system direction finder to the earth topocentric system of coordinates can be changed. The change in the position of the aerial system influences the accuracy of calculating the bearings. The method to reduce the errors of bearing by iteration method is considered. The checking procedure of the algorithm by mathematical modelling is carried out.


Author(s):  
В.Н. ЮДИН ◽  
А.М. ВОЛКОВ

Выведены формульные соотношения для расчета ошибок пеленгования парного излучателя с использованием разностно-фазового пеленгатора. Оценено влияние различных параметров парного излучателя на величину ошибки пеленгования этого излучателя. Formula relations for calculating the direction finding errors of a paired transmitter using a phase difference direction finder are derived. The influence of various parameters of a paired radiator on the magnitude of the direction finding error of this radiator is estimated.


Author(s):  
V. P. Denisov ◽  
◽  
D. V. Dubinin ◽  
D. V. Erofeev ◽  
◽  
...  

Author(s):  
Weihai Sun ◽  
Lemei Han

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.


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