公开(公告)号：US20220326016A1

公开(公告)日：2022-10-13

申请号：US17843451

申请日：2022-06-17

Applicant: Harbin Engineering University

Inventor： Yuxin Zhao ,  Bo Xu ,  Yu Guo ,  Lei Wu ,  Junmiao Hu ,  Chong Chen ,  Lianzhao Wang ,  Shengxin Li ,  Xiaoyu Wang ,  Zhaoyang Wang

IPC: G01C21/16

Abstract: The disclosure belongs to the technical field of integrated navigation under non-ideal conditions, and in particular relates to a robust filtering method for integrated navigation based on a statistical similarity measure (SSM). In view of the situation that there are normal beam measurement information of the DVL and beam measurement information with a large error simultaneously in a SINS/DVL tightly integrated system, and aiming at the problem that the existing robust filters of an integrated navigation system process the measurement information in a rough manner and are likely to lead to loss of normal measurement information, the disclosure proposes a novel robust filtering method based on decomposition of multi-dimensional measurement equations and the SSM. The disclosure introduces the SSM theory while decomposing the multi-dimensional measurement equations of the SINS/DVL tightly integrated navigation system, and assists the measurement noise variance of each beam to complete respective adaptive update in case of a large measurement error, finally ensuring independence of processing of the measurement information of each beam. The disclosure can be used in the field of integrated navigation of underwater vehicles under non-ideal conditions.

公开(公告)号：US10439594B2

公开(公告)日：2019-10-08

申请号：US15519823

申请日：2014-12-01

Applicant: Yuxin Zhao ,  HARBIN ENGINEERING UNIVERSITY

Inventor： Yuxin Zhao ,  Chang Liu ,  Xuefeng Zhang ,  Liqiang Liu ,  Gang Li ,  Feng Gao ,  Ning Li ,  Zhifeng Shen ,  Zhenxing Zhang ,  Zhao Qi

IPC: G06F17/50 ,  H03H17/02

Abstract: The present invention provides an actually-measured marine environment data assimilation method based on sequence recursive filtering three-dimensional variation. The method includes: preprocessing actually-measured marine environment data; calculating a target function value; calculating a gradient value of a target function; calculating a minimum value of the target function; extracting space multi-scale information from the actually-measured data; and updating background field data to form a final data assimilation analysis field. The present invention improves the traditional recursive filtering three-dimensional variation method, and sequentially assimilates information with different scales, thereby effectively overcoming the problem that multi-scale information cannot be effectively extracted by a traditional three-dimensional variation method. A high-order recursive Gaussian filter is used, and a cascaded form of the high-order recursive filter is converted into a parallel structure, so that the recursive filtering process of the recursive Gaussian filter can be executed in parallel, and many problems caused by a cascaded filter are overcome.

公开(公告)号：US20220326019A1

公开(公告)日：2022-10-13

申请号：US17846128

申请日：2022-06-22

Applicant: Harbin Engineering University

Inventor： Yuxin Zhao ,  Tingxiao Wei ,  Yueyang Ben ,  Lei Wu ,  Qian Li ,  Guangtao Zhou ,  Qianqian Gao ,  Xiaofeng Wei ,  Shuaiyang Li

IPC: G01C21/20 ,  G01C21/16

Abstract: The disclosure discloses a strapdown inertial navigation heave measurement method using multiple low-pass filter units, including: firstly, collecting data of a gyroscope and an accelerometer by a system, obtaining attitude information of a carrier by using initial alignment, and then, obtaining a relationship matrix between a body coordinate system and a geographic coordinate system by using the attitude information; obtaining a relationship matrix between the geographic coordinate system and a semi-fixed coordinate system according to a geographic position, and obtaining a rough vertical acceleration by using a direction cosine matrix, output information of the accelerometer and gravity information; then, filtering out low-frequency signals by using a double-filter unit and one integral link to obtain a relatively accurate velocity signal; and furthermore, enabling the vertical acceleration to be subjected to a triple-filter unit and two integral links to obtain an accurate heave displacement. The method avoids the problem of phase lead caused by traditional addition of high-pass filters, and can provide a reference for ship swaying reduction operations, ship carrier lifts, ship-borne weapon launch and heave compensation of various offshore platforms.

公开(公告)号：US12061087B2

公开(公告)日：2024-08-13

申请号：US17846128

申请日：2022-06-22

Applicant: Harbin Engineering University

Inventor： Yuxin Zhao ,  Tingxiao Wei ,  Yueyang Ben ,  Lei Wu ,  Qian Li ,  Guangtao Zhou ,  Qianqian Gao ,  Xiaofeng Wei ,  Shuaiyang Li

IPC: G01C21/20 ,  G01C21/16

CPC classification number: G01C21/203 ,  G01C21/16

Abstract: A strapdown inertial navigation heave measurement method using multiple low-pass filter units includes: firstly, collecting data of a gyroscope and an accelerometer by a system, obtaining attitude information of a carrier by using initial alignment, and then, obtaining a relationship matrix between a body coordinate system and a geographic coordinate system by using the attitude information; obtaining a relationship matrix between the geographic coordinate system and a reference coordinate system according to a geographic position, and obtaining a rough vertical acceleration by using a direction cosine matrix, output information of the accelerometer and gravity information; then, filtering out low-frequency signals by using a first filter unit and integration to obtain a relatively accurate velocity signal; and furthermore, enabling the vertical acceleration to be subjected to a second filter unit and integration to obtain an accurate heave displacement.

公开(公告)号：US20220326017A1

公开(公告)日：2022-10-13

申请号：US17844224

申请日：2022-06-20

Applicant: Harbin Engineering University

Inventor： Yuxin Zhao ,  Shuaiyang Li ,  Yueyang Ben ,  Lei Wu ,  Qian Li ,  Guangtao Zhou ,  Xinle Zang ,  Tingxiao Wei ,  Jiancheng Wang ,  Yifan Zhou

IPC: G01C21/16 ,  G01C21/18

Abstract: Disclosed is a self-adaptive horizontal attitude measurement method based on motion state monitoring. Based on a newly established state space model, a horizontal attitude angle is taken as a state variable, an angular velocity increment Δωb for compensating a random constant zero offset is taken as a control input of a system equation, and a specific force fb for compensating the random constant zero offset is taken as a measurement quantity. Meanwhile, judgment conditions for a maneuvering state of a carrier are improved, and maneuvering information of the carrier is judged by comprehensively utilizing acceleration information and angular velocity information output by a micro electro mechanical system inertial measurement unit (MEMS-IMU), whereby a measurement noise matrix of a filter can be automatically adjusted, thereby effectively reducing the influence of carrier maneuvering on the calculation of a horizontal attitude. The method has no special requirement on the maneuvering state of the carrier, and can ensure that the system has high attitude measurement precision in different motion states without an external information assistance.

公开(公告)号：US20170338802A1

公开(公告)日：2017-11-23

申请号：US15519823

申请日：2014-12-01

Applicant: HARBIN ENGINEERING UNIVERSITY

Inventor： Yuxin Zhao ,  Chang Liu ,  Harbin, Heilongjiang Zhang ,  Liqiang Liu ,  Gang Li ,  Feng Gao ,  Ning Li ,  Zhifeng Shen ,  Zhenxing Zhang ,  Zhao Qi

IPC: H03H17/02

CPC classification number: H03H17/0282 ,  G06F17/50 ,  H03H17/0202 ,  H03H2017/021

Abstract: The present invention provides an actually-measured marine environment data assimilation method based on sequence recursive filtering three-dimensional variation. The method includes: preprocessing actually-measured marine environment data; calculating a target function value; calculating a gradient value of a target function; calculating a minimum value of the target function; extracting space multi-scale information from the actually-measured data; and updating background field data to form a final data assimilation analysis field. The present invention improves the traditional recursive filtering three-dimensional variation method, and sequentially assimilates information with different scales, thereby effectively overcoming the problem that multi-scale information cannot be effectively extracted by a traditional three-dimensional variation method. A high-order recursive Gaussian filter is used, and a cascaded form of the high-order recursive filter is converted into a parallel structure, so that the recursive filtering process of the recursive Gaussian filter can be executed in parallel, and many problems caused by a cascaded filter are overcome.

公开(公告)号：US12140581B2

公开(公告)日：2024-11-12

申请号：US17847496

申请日：2022-06-23

Applicant: Harbin Engineering University

Inventor： Yuxin Zhao ,  Rixu Hao ,  Jiaxun Li ,  Chang Liu ,  Qiuyang Zhang ,  Dequan Yang ,  Shuo Yang ,  Yanlong Liu ,  Hengde Zhao ,  Ting Zhao

IPC: G01N33/18 ,  G01C13/00

Abstract: A method for a three-dimensional temperature and salinity field, including: based on multi-source marine environmental data, analyzing the spatiotemporal distribution characteristics of marine dynamic environmental elements, and studying the characteristics of the temperature-salinity relation; on the basis of analysis of the spatiotemporal characteristics and study of the characteristics of the temperature-salinity relation, establishing a statistical prediction model of marine environmental dynamic elements by a spatiotemporal empirical orthogonal function method; based on the observation data of temperature and salinity obtained by the marine transportation platform, correcting a marine environment forecast field around the marine transportation platform by using a realtime analysis technology of a marine environment field; and adjusting the salinity using a temperature-salinity relation curve after the temperature and salinity are forecasted.

公开(公告)号：US12061086B2

公开(公告)日：2024-08-13

申请号：US17844224

申请日：2022-06-20

Applicant: Harbin Engineering University

Inventor： Yuxin Zhao ,  Shuaiyang Li ,  Yueyang Ben ,  Lei Wu ,  Qian Li ,  Guangtao Zhou ,  Xinle Zang ,  Tingxiao Wei ,  Jiancheng Wang ,  Yifan Zhou

IPC: G01C21/16 ,  G01C21/18

CPC classification number: G01C21/188 ,  G01C21/18

Abstract: Disclosed is a self-adaptive horizontal attitude measurement method based on motion state monitoring. Based on a newly established state space model, a horizontal attitude angle is taken as a state variable, an angular velocity increment Δωb for compensating a random constant zero offset is taken as a control input of a system equation, and a specific force fb for compensating the random constant zero offset is taken as a measurement quantity. Meanwhile, judgment conditions for a maneuvering state of a carrier are improved, and maneuvering information of the carrier is judged by comprehensively utilizing acceleration information and angular velocity information output by a micro electro mechanical system inertial measurement unit (MEMS-IMU), whereby a measurement noise matrix of a filter can be automatically adjusted, thereby effectively reducing the influence of carrier maneuvering on the calculation of a horizontal attitude. The method has no special requirement on the maneuvering state of the carrier, and can ensure that the system has high attitude measurement precision in different motion states without an external information assistance.

公开(公告)号：US12104908B2

公开(公告)日：2024-10-01

申请号：US17843451

申请日：2022-06-17

Applicant: Harbin Engineering University

Inventor： Yuxin Zhao ,  Bo Xu ,  Yu Guo ,  Lei Wu ,  Junmiao Hu ,  Chong Chen ,  Lianzhao Wang ,  Shengxin Li ,  Xiaoyu Wang ,  Zhaoyang Wang

IPC: G01C21/16

CPC classification number: G01C21/1652

Abstract: The disclosure belongs to the technical field of integrated navigation under non-ideal conditions, and in particular relates to a robust filtering method for integrated navigation based on a statistical similarity measure (SSM). In view of the situation that there are normal beam measurement information of the DVL and beam measurement information with a large error simultaneously in a SINS/DVL tightly integrated system, and aiming at the problem that the existing robust filters of an integrated navigation system process the measurement information in a rough manner and are likely to lead to loss of normal measurement information, the disclosure proposes a novel robust filtering method based on decomposition of multi-dimensional measurement equations and the SSM. The disclosure introduces the SSM theory while decomposing the multi-dimensional measurement equations of the SINS/DVL tightly integrated navigation system, and assists the measurement noise variance of each beam to complete respective adaptive update in case of a large measurement error, finally ensuring independence of processing of the measurement information of each beam. The disclosure can be used in the field of integrated navigation of underwater vehicles under non-ideal conditions.

公开(公告)号：US20220326211A1

公开(公告)日：2022-10-13

申请号：US17847496

申请日：2022-06-23

Applicant: Harbin Engineering University

Inventor： Yuxin Zhao ,  Rixu Hao ,  Jiaxun Li ,  Chang Liu ,  Qiuyang Zhang ,  Dequan Yang ,  Shuo Yang ,  Yanlong Liu ,  Hengde Zhao ,  Ting Zhao

IPC: G01N33/18 ,  G01C13/00

Abstract: The disclosure provides a marine transportation platforms guarantee-oriented analysis and prediction method for a three-dimensional temperature and salinity field, including: based on multi-source marine environmental data, analyzing the spatiotemporal distribution characteristics of marine dynamic environmental elements, and studying the characteristics of the temperature-salinity relation; on the basis of analysis of the spatiotemporal characteristics and study of the characteristics of the temperature-salinity relation, establishing a statistical prediction model of marine environmental dynamic elements by a spatiotemporal empirical orthogonal function method; based on the observation data of temperature and salinity obtained by the marine transportation platform, correcting a marine environment forecast field around the marine transportation platform by using a realtime analysis technology of a marine environment field; and adjusting the salinity using a temperature-salinity relation curve after the temperature and salinity are forecasted, so as to keep the temperature-salinity relation as close as possible to its climatic characteristics. The disclosure makes up for the shortcomings of the traditional numerical prediction method that the period of prediction validity of marine dynamic environmental elements is short due to meteorologically driven timeliness restrictions, and the prediction process of the disclosure does not require a high-performance computing platform and occupies less computing resource.