Inertial navigation apparatus and method to which composite navigation algorithm suitable for marine environment is applied

Abstract

An inertial navigation system and apparatus to which a composite navigation algorithm suitable for a marine environment is applied, according to an embodiment, estimate, on the basis of a composite navigation system combining GPS navigation, EM-Log and INS navigation, the position and attitude of a ship by applying an algorithm capable of processing a marine environment and various obstacle factors. In addition, the inertial navigation system and apparatus to which a composite navigation algorithm suitable for a marine environment is applied, according to an embodiment, perform initial alignment for calculating the attitude of a ship, and apply a pure inertial navigation algorithm on the basis of initial position and attitude data. Afterward, ship position and attitude estimation, including a step of applying a composite inertial navigation algorithm to which GPS navigation and EM-Log navigation are applied, is performed.

Description

Inertial navigation device and method applying a composite navigation algorithm suitable for the marine environment

[0001] The present disclosure relates to an inertial navigation system and device that applies a composite navigation algorithm suitable for a marine environment, and more specifically, to a system and device that estimates the position and attitude of a ship by applying an algorithm capable of handling the marine environment and various interference factors.

[0002] Unless otherwise indicated herein, the materials described in this section are not prior art to the claims of this application, and their inclusion in this section is not intended to be admitted as prior art.

[0003] An inertial navigation system (INS) is a device that measures inertial force using a gyro sensor and acceleration using an acceleration sensor to calculate the speed, direction, and distance of a moving target, thereby providing various navigation-related information. Unlike the land surface, the marine environment is fluid due to various factors such as water velocity and waves. Therefore, when data is detected through an inertial navigation device, errors occur depending on the marine environment, making it difficult to derive accurate navigation data.

[0004] An inertial navigation system (INS) consists of an accelerometer, which measures the acceleration of a moving object, a gyroscope, which detects the rotation angle of the aircraft, and an electronic circuit that processes the measured information to calculate the spatial position and attitude of the moving object. An INS is a navigation system that determines the position, velocity, and attitude of an aircraft without the assistance of external devices. It provides relatively accurate position information without being affected by radio interference or the environment. However, conventional INS suffers from a problem in that errors increase significantly over time. Typically, a hybrid navigation system that combines the Global Positioning System (GPS) and INS navigation is configured to address the issues of INS.

[0005] For ships, various marine environments, such as waves and water speed, can affect navigation data, causing errors. Furthermore, GPS sensors or EM log sensors are typically external sensors installed outside the vessel, while the Inertial Reference Unit (IRU) is a device installed inside the vessel. This creates a difference in measured position between the GPS, EM log, and IRU, resulting in position and velocity errors. This indirectly impacts the estimation of the vessel's attitude and inertial sensor bias, hindering accurate navigation solutions.

[0006] An inertial navigation system and device applying a composite navigation algorithm suitable for a marine environment according to an embodiment is based on a composite navigation system that combines GPS navigation, EM-Log, and INS navigation, and estimates the position and attitude of a ship by applying an algorithm that can process the marine environment and various interference factors.

[0007] Additionally, the inertial navigation system and device, which employ a composite navigation algorithm suitable for the marine environment according to the embodiment, performs an initial alignment to calculate the ship's attitude and applies a pure inertial navigation algorithm based on the initial position and attitude data. Subsequently, the vessel's position and attitude are estimated, including a step of applying a composite inertial navigation algorithm utilizing GPS navigation and EM-Log navigation.

[0008] Additionally, in the embodiment, the measurement error can be corrected by including the influence of the lever arm in the EM log complex Kalman filter model and the measurement model.

[0009] However, the problems to be solved according to one embodiment are not limited to those mentioned above.

[0010] A method for estimating a ship's position using a composite navigation algorithm suitable for a marine environment according to an embodiment includes: (A) an initial alignment step for calculating the ship's attitude; (B) a step for performing inertial navigation based on initial position and attitude data; and (C) a step for estimating the ship's position and attitude by performing composite inertial navigation using GPS data and EM log data.

[0011] In addition, step (A) can perform an initial alignment process for calculating the attitude of the ship before entering the navigation mode through an IMU inertial navigation system using a three-axis inertial sensor composed of a high-performance gyro interferometer using optical fiber.

[0012] In addition, step (A); can feed back the Kalman filter through a precision alignment algorithm using the Kalman filter and correct the error using the fed-back Kalman filter.

[0013] In addition, step (B); applies a pure inertial navigation algorithm using the initial position and attitude information of the ship, thereby enabling calculation of the attitude, position, acceleration, and angular velocity of the ship.

[0014] In addition, step (C); the difference between the navigation solutions obtained from each of INS and GPS is used as a measurement value of the Kalman filter, and the filter can be configured with an indirect feedback structure that compensates for the INS error with the error estimated from the Kalman filter.

[0015] In addition, step (C); uses GPS as a primary auxiliary sensor to correct the accumulated error of the inertial navigation system, and may use an EM log data sensor as an auxiliary sensor when GPS reception is not possible in some sections.

[0016] In addition, step (C); estimates the sea velocity using EM log data measuring the logarithmic velocity, implements composite navigation using the sum of the sea velocity and the logarithmic velocity, and the EM log composite navigation is also configured with the same indirect feedback structure as GPS so that the INS error can be compensated for with the error estimated from the Kalman filter.

[0017]

[0018] The inertial navigation system and device that apply the composite navigation algorithm suitable for the marine environment as described above solves the problem of significant increase in error over time in the inertial navigation system, thereby enabling more accurate estimation of the ship's position and attitude.

[0019] In addition, the inertial navigation system and device applying a composite navigation algorithm suitable for the marine environment according to the embodiment efficiently fuses the inertial navigation position information defined on the ship, GPS position, and EM-Log information to estimate the position and attitude of the ship, thereby improving data processing efficiency and estimation accuracy.

[0020] Additionally, the composite navigation algorithm according to the embodiment integrates various sensor data, including GPS, inertial sensors, and barometric pressure sensors, to provide more accurate positioning and navigation information. This enables the vessel to maintain an accurate course and move in a predictable manner.

[0021] Furthermore, the inertial navigation system according to the embodiment is relatively less affected by the external environment. It overcomes some of the limitations of existing radar and GPS systems, providing stable navigation, thereby enhancing the safety of vessel operation even in adverse weather conditions.

[0022] In addition, the composite navigation algorithm according to the embodiment supports a ship to autonomously maintain a certain route, which can contribute to the development of autonomous ships or unmanned ships.

[0023] Additionally, in the embodiment, accurate position and navigation information can enable ships to select optimal routes and minimize fuel consumption, thereby enabling economical operation and contributing to environmentally friendly operation.

[0024] Additionally, the embodiment utilizes the integration of various sensors to accommodate operating conditions in diverse marine environments. For example, inertial sensors can be utilized to maintain accurate positioning information even in areas with weak GPS signals.

[0025] The effects of the present invention are not limited to the effects described above, and should be understood to include all effects that can be inferred from the detailed description of the present invention or the composition of the invention described in the claims.

[0026]

[0027] Figure 1 is a drawing showing the configuration of an inertial navigation device that applies a composite navigation algorithm suitable for a marine environment according to an embodiment.

[0028] Figure 2 is a diagram showing the data processing process of a ship position estimation method using a composite navigation algorithm suitable for a marine environment according to an embodiment.

[0029]

[0030] A method for estimating a ship's position using a composite navigation algorithm suitable for a marine environment according to an embodiment includes: (A) an initial alignment step for calculating the ship's attitude; (B) a step for performing inertial navigation based on initial position and attitude data; and (C) a step for estimating the ship's position and attitude by performing composite inertial navigation using GPS data and EM log data.

[0031]

[0032] Hereinafter, the embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Regardless of the drawing numbers, identical or similar components will be given the same reference numbers, and redundant descriptions thereof will be omitted. The suffixes "module" and "part" used for components in the following description are assigned or used interchangeably only for the convenience of writing the specification, and do not in themselves have distinct meanings or roles. In addition, when describing the embodiments disclosed in this specification, if it is determined that a specific description of a related known technology may obscure the gist of the embodiments disclosed in this specification, a detailed description thereof will be omitted. In addition, the attached drawings are only intended to make it easier to understand the embodiments disclosed in this specification, and the technical ideas disclosed in this specification are not limited by the attached drawings, and it should be understood that they include all modifications, equivalents, and substitutes included in the spirit and technical scope of the present invention.

[0033] Terms that include ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by these terms. These terms are used solely to distinguish one component from another.

[0034] When a component is referred to as being "connected" or "connected" to another component, it should be understood that it may be directly connected or connected to that other component, but that there may be other components intervening. Conversely, when a component is referred to as being "directly connected" or "connected" to another component, it should be understood that there are no other components intervening.

[0035] In this application, terms such as “include” or “have” are intended to specify the presence of a feature, number, step, operation, component, part or combination thereof described in the specification, but should be understood not to exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts or combinations thereof.

[0036] In this specification, the term "unit" includes a unit realized by hardware, a unit realized by software, and a unit realized using both. Furthermore, a single unit may be realized using two or more pieces of hardware, and two or more units may be realized by a single piece of hardware.

[0037] Some of the operations or functions described herein as being performed by a terminal, apparatus, or device may instead be performed by a server connected to the terminal, apparatus, or device. Similarly, some of the operations or functions described herein as being performed by a server may also be performed by a terminal, apparatus, or device connected to the server.

[0038] Hereinafter, the present invention will be described in detail with reference to the attached drawings.

[0039] Figure 1 is a drawing showing the configuration of an inertial navigation device that applies a composite navigation algorithm suitable for a marine environment according to an embodiment.

[0040] Referring to FIG. 1, an inertial navigation device applying a complex navigation algorithm suitable for a marine environment according to an embodiment may be configured to include a control board (110), an IMU (140), and an interface unit (150), and the control board may be configured to include an FPGA and a DSP. The term 'unit' used in this specification should be interpreted to include software, hardware, or a combination thereof, depending on the context in which the term is used. For example, the software may be machine language, firmware, embedded code, and application software. As another example, the hardware may be a circuit, a processor, a computer, an integrated circuit, an integrated circuit core, a sensor, a MEMS (Micro-Electro-Mechanical System), a passive device, or a combination thereof.

[0041] The IMU (Inertial Measurement Unit, 140) is an inertial measurement device and includes an accelerometer and a gyroscope. Each sensor senses and provides information on the movement and rotation of the ship and transmits the sensed information to the interface unit (150). The interface unit (150) transmits the information on the movement and rotation of the ship received from the IMU (140) to the FPGA of the control board (110). In addition, the interface unit (150) transmits external data to the FPGA (120). In an embodiment, the external data may include GPS data and EM log data. The EM log data is electromagnetic (EM) logging or measurement data. The EM log data includes the results of recording or measuring information on an electromagnetic field. The FPGA (Field-Programmable Gate Array, 120) is a semiconductor device that allows a user to program a digital logic circuit to perform a desired digital logic function. Unlike ASIC (Application-Specific Integrated Circuit), this provides flexibility for implementing the logic circuit desired by the user without changing the manufacturing process or mask, etc. The FPGA (120) transmits the movement and rotation data of the ship processed by the INS algorithm of the DSP (111) and transmits the EM log data and GPS data to the external data processing unit (113). In the embodiment, the INS algorithm performs the initial alignment, pure inertial navigation, and composite inertial navigation processes. In the embodiment, composite inertial navigation is performed using external data transmitted from the external data processing unit (113).

[0042] In the embodiment, based on a composite navigation system that combines GPS, EM log data, and INS navigation, a composite navigation algorithm capable of processing the marine environment and various interference factors is applied to estimate the position and attitude of a ship.

[0043] In an embodiment, an inertial navigation device applying a composite navigation algorithm may include an initial alignment step for calculating the attitude of a ship, a step of applying a pure inertial navigation algorithm based on initial position and attitude data, and a step of applying a composite inertial navigation algorithm applying GSP navigation and EM-Log navigation.

[0044] In the embodiment, the position and attitude of a ship are estimated by efficiently fusing inertial navigation position information, GPS position, and EM log information. For example, an IMU inertial navigation system using a three-axis inertial sensor composed of a high-performance gyro interferometer using optical fiber performs an initial alignment process to calculate the attitude of the ship before entering navigation mode. In the embodiment, in order to reduce the influence of disturbances during attitude estimation, an alignment algorithm is implemented using a relational expression in an inertial coordinate system (i-frame), and the alignment algorithm is applied to finally obtain a value from a body frame to a navigation frame to calculate the attitude of the ship.

[0045] In this embodiment, a precise alignment algorithm using a Kalman filter is used to more accurately estimate the posture estimated through the alignment algorithm. In this embodiment, errors can be corrected using a Kalman filter with a feedback structure. This results in more accurate velocity and posture data.

[0046] Afterwards, the inertial navigation device applying the composite navigation algorithm goes through a step of applying a pure inertial navigation algorithm using the ship's initial position and attitude information. At this time, the reference coordinate system for navigation calculations is selected as the NED navigation coordinate system. In the embodiment, the inertial navigation device applying the composite navigation algorithm is a strapdown inertial navigation system, and calculates the ship's attitude, position, acceleration, and angular velocity.

[0047] Conventional inertial navigation systems have a problem in that errors increase significantly over time. Therefore, in order to compensate for this, the embodiment applies a composite inertial navigation algorithm that combines GPS and EM log data into navigation. The GPS composite navigation method configures a filter with an indirect feedback structure using a 15th-order loosely coupled method. The 15th-order loosely coupled method provided in the embodiment is a method for estimating a position by combining various sensors and information. Here, the 15th order represents the order of the filter, and the filter is a mathematical model used for estimation and correction. The indirect feedback structure is a process in which feedback from the filter compares the predicted result with the current state to correct the system. The indirect feedback structure is a structure in which correction is performed indirectly, where the difference between the navigation solutions obtained from the INS and GPS is used as a measurement value of the Kalman filter, and the filter is configured with an indirect feedback structure that compensates for the INS error with the error estimated by the Kalman filter.

[0048] In the embodiment, GPS is used as the primary auxiliary sensor to compensate for the accumulated error of the inertial navigation system. However, in some sections where GPS reception is unavailable, an EM log data collection unit is used as an auxiliary sensor. In the embodiment, seawater velocity is estimated using EM log data measuring seawater velocity and GPS data measuring ground velocity. In the embodiment, composite navigation is implemented by calculating the seawater velocity value and the sum of the seawater velocity and seawater velocity. The composite navigation using EM log data is also configured with the same indirect feedback structure as GPS to compensate for the INS error with the error estimated by the Kalman filter.

[0049] When operating a composite inertial navigation system using external sensors such as GPS or EM-Log, the installation locations of each sensor and IRU vary, resulting in differences in the measurement reference position. This is called a lever arm error, which indirectly affects the estimation of the ship's attitude and inertial sensor bias, making it impossible to obtain a correct navigation solution. In this embodiment, the influence of the lever arm is included in the GPS and EM-Log composite Kalman filter system model and the measurement model to correct the error caused by the lever arm.

[0050] To achieve this, the Kalman filter system models state information. This modeling involves modeling the dynamic characteristics of the system, which may include the ship's position, velocity, and acceleration. Next, a measurement model is used to determine the relationship between the measurements obtained from sensors and the state model. In the embodiment, the measurements include GPS and EM-Log measurements. Then, modeling is performed, including the influence of the lever arm. In the embodiment, the influence of the lever arm is reflected in the state model and measurement model, thereby taking the influence of the lever arm into account in the ship's position estimation and error correction.

[0051] Next, the composite inertial navigation model according to the embodiment estimates the error caused by the lever arm and compensates for it using the measured values. In the embodiment, the position and measured values ​​from GPS and EM logs are used to calculate the expected error caused by the lever arm. The calculated expected error is then reflected in the state estimation to accurately estimate the actual position.

[0052] In the following example, the Kalman filter is used to estimate and predict the actual state.

[0053] When actual measurements arrive, the Kalman filter minimizes the error between the predicted state and the actual measurement and provides an updated state. In this embodiment, GPS and EM-Log are integrated to enable accurate position estimation while compensating for lever arm errors in real time.

[0054] Below, the methods are described in order. The operation (function) of the vessel position estimation method using a composite navigation algorithm suitable for the marine environment according to the embodiment is essentially the same as the function of the system, so any description overlapping with that in Figure 1 will be omitted.

[0055] Figure 2 is a diagram showing the data processing process of a ship position estimation method using a composite navigation algorithm suitable for a marine environment according to an embodiment.

[0056] Referring to Figure 2, in step S100, the ship's attitude is calculated and initially aligned.

[0057] At stage S100, the ship performs an initial alignment process using an IMU inertial navigation system comprised of a three-axis inertial sensor and a high-performance gyro-interferometer utilizing optical fiber. This process calculates the ship's attitude before entering navigation mode. Furthermore, stage S100 uses a precision alignment algorithm utilizing a Kalman filter to provide feedback on estimated errors and correct the feedback errors.

[0058] In step S200, inertial navigation is performed based on initial position and attitude data. In step S200, a pure inertial navigation algorithm is applied using the ship's initial position and attitude information to calculate the ship's attitude, position, acceleration, and angular velocity. In step S300, a composite inertial navigation using GPS data and EM log data is performed to estimate the ship's position and attitude. In step S300, GPS is used as the main auxiliary sensor to compensate for the accumulated error of the inertial navigation system, and the EM log data sensor is used as an auxiliary sensor when GPS reception is unavailable in some sections. In addition, in step S300, the sea velocity is estimated using the EM log data that measures the sea velocity, and the composite navigation is implemented using the sum of the sea velocity and the sea velocity. The EM log composite navigation is also configured with the same indirect feedback structure as GPS to compensate for the INS error with the error estimated by the Kalman filter.

[0059] The inertial navigation system and device that apply the composite navigation algorithm suitable for the marine environment as described above solves the problem of significant increase in error over time in the inertial navigation system, thereby enabling more accurate estimation of the ship's position and attitude.

[0060] In addition, the inertial navigation system and device applying a composite navigation algorithm suitable for the marine environment according to the embodiment efficiently fuses the inertial navigation position information defined on the ship, GPS position, and EM-Log information to estimate the position and attitude of the ship, thereby improving data processing efficiency and estimation accuracy.

[0061] Additionally, the composite navigation algorithm according to the embodiment integrates various sensor data, including GPS, inertial sensors, and barometric pressure sensors, to provide more accurate positioning and navigation information. This enables the vessel to maintain an accurate course and move in a predictable manner.

[0062] Furthermore, the inertial navigation system according to the embodiment is relatively less affected by the external environment. It overcomes some of the limitations of existing radar and GPS systems, providing stable navigation, thereby enhancing the safety of vessel operation even in adverse weather conditions.

[0063] In addition, the composite navigation algorithm according to the embodiment supports a ship to autonomously maintain a certain route, which can contribute to the development of autonomous ships or unmanned ships.

[0064] Additionally, in the embodiment, accurate position and navigation information can enable ships to select optimal routes and minimize fuel consumption, thereby enabling economical operation and contributing to environmentally friendly operation.

[0065] Additionally, the embodiment utilizes the integration of various sensors to accommodate operating conditions in diverse marine environments. For example, inertial sensors can be utilized to maintain accurate positioning information even in areas with weak GPS signals.

[0066] The disclosed content is merely an example, and various modifications and implementations can be made by a person skilled in the art without departing from the gist of the claims claimed in the patent, so the scope of protection of the disclosed content is not limited to the specific embodiments described above.

[0067]

[0068] The inertial navigation system and device that apply the composite navigation algorithm suitable for the marine environment as described above solves the problem of significant increase in error over time in the inertial navigation system, thereby enabling more accurate estimation of the ship's position and attitude.

[0069] In addition, the inertial navigation system and device applying a composite navigation algorithm suitable for the marine environment according to the embodiment efficiently fuses the inertial navigation position information defined on the ship, GPS position, and EM-Log information to estimate the position and attitude of the ship, thereby improving data processing efficiency and estimation accuracy.

[0070] Additionally, the composite navigation algorithm according to the embodiment integrates various sensor data, including GPS, inertial sensors, and barometric pressure sensors, to provide more accurate positioning and navigation information. This enables the vessel to maintain an accurate course and move in a predictable manner.

[0071] Furthermore, the inertial navigation system according to the embodiment is relatively less affected by the external environment. It overcomes some of the limitations of existing radar and GPS systems, providing stable navigation, thereby enhancing the safety of vessel operation even in adverse weather conditions.

[0072] In addition, the composite navigation algorithm according to the embodiment supports a ship to autonomously maintain a certain route, which can contribute to the development of autonomous ships or unmanned ships.

[0073] Additionally, in the embodiment, accurate position and navigation information can enable ships to select optimal routes and minimize fuel consumption, thereby enabling economical operation and contributing to environmentally friendly operation.

[0074] Additionally, the embodiment utilizes the integration of various sensors to accommodate operating conditions in diverse marine environments. For example, inertial sensors can be utilized to maintain accurate positioning information even in areas with weak GPS signals.

[0075]

[0076] 100: Inertial Navigation System

Claims

1. A method for estimating a ship's position using a composite navigation algorithm suitable for the marine environment. (A) Initial alignment step for calculating the attitude of the vessel; (B) a step of performing inertial navigation based on initial position and attitude data; and (C) A step of estimating the position and attitude of a ship by performing a composite inertial navigation using GSP data and EM log data; An inertial navigation method including; 2. In the first paragraph, the step (A); An inertial navigation method characterized by performing an initial alignment process for calculating the attitude of a ship before entering navigation mode using an IMU inertial navigation system comprising a three-axis inertial sensor composed of a high-performance gyro interferometer using optical fiber.

3. In the second paragraph, the step (A); An inertial navigation method characterized by feeding back an estimation error and correcting the fed-back error through a precision alignment algorithm using a Kalman filter.

4. In the first paragraph, the step (B); An inertial navigation method characterized by calculating the attitude, position, acceleration, and angular velocity of a ship by applying a pure inertial navigation algorithm using the ship's initial position and attitude information.

5. In the first paragraph, the step (C); An inertial navigation method characterized in that the difference between navigation solutions obtained from each of INS and GPS is used as a measurement value of a Kalman filter, and the filter is configured with an indirect feedback structure that compensates for the INS error with the error estimated from the Kalman filter.

6. In the fifth paragraph, the step (C); An inertial navigation method characterized by using GPS as a primary auxiliary sensor to correct accumulated errors of an inertial navigation system and using an EM log data sensor as an auxiliary sensor when GPS reception is impossible in some sections.

7. In the 6th paragraph, the step (C); An inertial navigation method characterized by estimating sea velocity using EM log data measuring sea velocity, implementing composite navigation using the sum of sea velocity and logarithmic velocity, and compensating for INS error with an error estimated from a Kalman filter by configuring the EM log composite navigation with the same indirect feedback structure as GPS.

Images