公开(公告)号：US20240145911A1

公开(公告)日：2024-05-02

申请号：US17989638

申请日：2022-11-17

Applicant: AUDEN TECHNO CORP.

Inventor： YUNG-TAI HSU ,  CHUN-HENG CHAO ,  YEN-WEI WANG ,  BO-YU ZHU

IPC: H01Q3/26 ,  H04B17/12

CPC classification number: H01Q3/26 ,  H04B17/12

Abstract: An antenna correcting system is provided. The antenna correction system compares amplitudes of antenna signals that are emitted or received respectively by a plurality of antenna units with each other to select one of the amplitudes as target amplitude. The antenna correction system corrects the amplitude of each of the antenna signals according to the target amplitude. As a result, the amplitudes of the antenna signals are the same as each other or approximate to each other. After the amplitudes of the antenna signals are corrected, the antenna correction system compares phases of the antenna signals with each other to select one of the phases as a target phase. The antenna correction system corrects the phase of each of the antenna signals according to the target phase. As a result, the phases of the antenna signals are the same as each other or approximate to each other.

公开(公告)号：US20240192692A1

公开(公告)日：2024-06-13

申请号：US18064999

申请日：2022-12-13

Applicant: AUDEN TECHNO CORP.

Inventor： YUNG-TAI HSU ,  CHUN-HENG CHAO ,  YEN-WEI WANG ,  BO-YU ZHU

IPC: G05D1/08 ,  G06F17/18

CPC classification number: G05D1/0891 ,  G06F17/18 ,  G05D2201/0213

Abstract: A heading and attitude correction method and a heading and attitude correction system are provided. The method includes: obtaining attitude data in a period of time; performing a linear regression analysis on the attitude data and time points in the time period to obtain a regression line and a standard deviation; obtaining a deviation value between the attitude data and the regression line at each of the time points; excluding the attitude data for which the deviation value is greater than or equal to at least twice the standard deviation; grouping the attitude data according to a grouping value to form clusters; comparing a total quantity of the attitude data in each of the clusters, and defining one of the clusters with a largest total quantity as an ideal cluster; and calculating an average of the attitude data in the ideal cluster as a reasonable attitude data.