Proposal of sound source position estimation method by portable sound direction estimation device

Author(s):  
Yuki KANDA ◽  
Katsuyuki ONISHI ◽  
Makoto ISOGAWA ◽  
Yoshihisa UCHIDA
2019 ◽  
Vol 33 (7-8) ◽  
pp. 403-414 ◽  
Author(s):  
D. Gabriel ◽  
R. Kojima ◽  
K. Hoshiba ◽  
K. Itoyama ◽  
K. Nishida ◽  
...  

2016 ◽  
Vol 13 (10) ◽  
pp. 7319-7323
Author(s):  
Mei Yun

How to improve the performance of multiple sound source localization method, this paper studies the parameter and process design in multiple sound source position. First, it divides a signal into several sub-frames, and it calculates signal variation; then it uses the clustering algorithm to divide the estimated values into several categories; finally it calculates the final sound source location estimation. Experimental results show that the positioning algorithm is effective. There are many parameters will affect the gunfire correct rate and error rate, the parameters and angle selection will affect sound source position estimation.


2021 ◽  
Vol 13 (15) ◽  
pp. 2997
Author(s):  
Zheng Zhao ◽  
Weiming Tian ◽  
Yunkai Deng ◽  
Cheng Hu ◽  
Tao Zeng

Wideband multiple-input-multiple-output (MIMO) imaging radar can achieve high-resolution imaging with a specific multi-antenna structure. However, its imaging performance is severely affected by the array errors, including the inter-channel errors and the position errors of all the transmitting and receiving elements (TEs/REs). Conventional calibration methods are suitable for the narrow-band signal model, and cannot separate the element position errors from the array errors. This paper proposes a method for estimating and compensating the array errors of wideband MIMO imaging radar based on multiple prominent targets. Firstly, a high-precision target position estimation method is proposed to acquire the prominent targets’ positions without other equipment. Secondly, the inter-channel amplitude and delay errors are estimated by solving an equation-constrained least square problem. After this, the element position errors are estimated with the genetic algorithm to eliminate the spatial-variant error phase. Finally, the feasibility and correctness of this method are validated with both simulated and experimental datasets.


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