Independent task-based simulation system and method for inertial sensor aircraft

Abstract

An inertial sensor aircraft simulation system according to one embodiment of the technical concept of the present disclosure comprises: a plurality of independent tasks each configured to execute one of a 6-degrees-of-freedom equations of motion model, an inertial navigation system (INS) model, a guidance control unit (GCU) model, and an actuator model, each having a respective computation cycle; a communication module for data transmission between the plurality of independent tasks; a clock synchronization device configured to synchronize the respective computation cycles of the plurality of independent tasks; and a processing device that manages the execution of the plurality of independent tasks, calculates and applies a total INS delay including the communication time from the INS model to the flight attitude simulator (FMS), the physical response time of the FMS, and the difference in processing delay between the actual hardware and the simulation model, calculates and applies a guidance control unit delay for the GCU model, and calculates and applies an actuator delay for the actuator model.

Description

Technology Field

[0001] The technical concept of the present disclosure is to an independent task-based inertial sensor aircraft simulation system and method. Background Technology

[0002] Hardware-In-the-Loop Simulation (HWIL) is an essential step in the development and performance verification process of an aircraft. This process aims to simulate actual flight environments in a laboratory setting by utilizing core subsystems of the aircraft, such as inertial sensors, navigation computers, guidance and control systems, and actuators. Generally, software simulation programs developed to predict and control the movement of an aircraft calculate six-degree-of-freedom equations of motion in a real-time computer environment and perform calculations for each subsystem model. In HWIL simulations, where actual hardware components are used, the real-time computer solves only the six-degree-of-freedom equations of motion and verifies performance by exchanging necessary information through communication with each subsystem hardware.

[0003] However, in the early stages of aircraft development or when physical hardware for specific subsystems is not yet ready, all subsystem models are often implemented solely in simulation software and executed on a single computer. In such simulation environments, the 6-degrees-of-freedom equations of motion and each subsystem model tend to be processed sequentially in a serial manner. This presents a limitation in that it fails to properly reflect the fact that actual aircraft systems are distributed processing environments where multiple subsystems operate in parallel and asynchronously on independent processors or controllers and communicate with each other.

[0004] Consequently, the unique computational cycles of each subsystem and actual communication delays between subsystems are not sufficiently considered in the simulation environment, leading to significant discrepancies between the simulation results and actual flight data. This undermines the reliability of pre-verifying and predicting aircraft performance and can make it difficult to detect errors early during the development process.

[0005] In particular, for aircraft equipped with sensitive inertial sensors, minute computational and communication delays can have a significant impact on the closed-loop performance of the entire system. Therefore, there is a need to develop new simulation systems and methodologies capable of reliably predicting and verifying the closed-loop performance of aircraft by accurately simulating and compensating for the complex distributed processing characteristics and various forms of computational and communication delays of actual flight environments, even without physical hardware. The problem to be solved

[0006] The problem that the present disclosure aims to solve is to address the issue where the reliability of simulation results is reduced in a simulation environment where the closed-loop performance of an aircraft is predicted and verified in advance without the actual hardware being fully equipped, because existing simulation systems fail to sufficiently reflect the distributed processing characteristics of the actual flight environment, asynchronous operation between subsystems, and various computational and communication delays.

[0007] In particular, the invention provides a simulation system and method that effectively simulates and compensates for the impact of the unique computational cycles and communication delays of each subsystem on the closed-loop performance prediction accuracy of the entire system. means of solving the problem

[0008] To achieve the above objectives, an inertial sensor aircraft simulation system according to one aspect of the technical concept of the present disclosure comprises: a plurality of independent tasks each configured to execute one of a 6-degrees-of-freedom equations of motion model, an inertial navigation system (INS) model, a guidance control unit (GCU) model, and an actuator model, each having a respective computational cycle; a communication module for data transmission between the plurality of independent tasks; a clock synchronization device configured to synchronize the computational cycles of the plurality of independent tasks; and a processing unit configured to manage the execution of the plurality of independent tasks. The processing unit is configured to calculate and apply a total inertial navigation system (INS) delay, which includes the communication time from the INS model to the flight attitude simulator (FMS), the physical response time of the FMS, and the difference in processing delay between the actual hardware and the simulation model. Additionally, the processing unit is configured to calculate and apply a guidance control unit delay for the GCU model and to calculate and apply an actuator delay for the actuator model.

[0009] According to one embodiment, the communication module may be configured to perform data transmission between the plurality of independent tasks using an asynchronous shared memory. In this case, the asynchronous shared memory may include a VME (VERSA Module Eurocard) shared memory.

[0010] According to one embodiment, the processing device may be optionally configured to measure an angular velocity value through the FMS or to calculate an angular velocity value through an angular velocity sensor model. When the processing device measures an angular velocity value through the FMS, it may be configured to execute a transformation algorithm that mutually transforms the coordinate systems of the data when exchanging data between the FMS and one or more of the INS model or the 6-degrees-of-freedom equations of motion model, if the coordinate system used in the FMS is different from the coordinate system used in the other model. The transformation algorithm may include an operation to convert Euler angular velocity into Euler angles.

[0011] According to one embodiment, the clock synchronization device may be configured to synchronize the operation cycles of the plurality of independent tasks through a clock generated by a simulation computer.

[0012] According to one embodiment, the processing device may be configured to transmit an angular velocity value derived from the 6-degree-of-freedom equation of motion model to the FMS through a converter, and to receive the angular velocity value from the FMS in the INS model to perform navigation calculations.

[0013] According to one embodiment, the processing device may be configured to handle the communication delay between the INS model and the FMS by compensating the calculated total INS delay to the data transmission period. Additionally, the processing device may be configured to handle the communication delay between the GCU model and the 6-degrees-of-freedom equation of motion model by compensating the calculated guidance control device delay to the data transmission period of the GCU model, and may be configured to handle the communication delay between the actuator model and the 6-degrees-of-freedom equation of motion model by compensating the calculated actuator delay to the data transmission period of the actuator model.

[0014] A simulation method for predicting the closed-loop performance of an inertial sensor aircraft according to one embodiment of the technical concept of the present disclosure comprises: a step of operating a plurality of independent tasks, each executing one of a 6-degrees-of-freedom equation of motion model, an INS model, a GCU model, and an actuator model; a step of transmitting data between the plurality of independent tasks; a step of synchronizing the operation cycle of each of the plurality of independent tasks through a clock generated by a simulation computer; a step of calculating and applying a total INS delay including the communication time from the INS model to the FMS, the physical response time of the FMS, and the difference in processing delay between the actual hardware and the simulation model; a step of calculating and applying a guidance control delay for the GCU model; and a step of calculating and applying an actuator delay for the actuator model. Effects of the invention

[0015] According to the technical concept of the present disclosure, by performing simulations by separating the 6-degree-of-freedom equations of motion and each subsystem model into independent tasks, the distributed processing environment and asynchronous operation characteristics of an actual aircraft system can be more faithfully simulated. This provides a basis for accurately reflecting the complex interactions and delay characteristics of the actual system in the simulation.

[0016] Furthermore, according to the present disclosure, it is possible to explicitly model and compensate for realistic communication delays occurring during the unique computation cycle of each subsystem model composed of independent tasks and the data exchange between tasks. In particular, the fidelity of the simulation can be maximized by compensating for the total delay time, which comprehensively considers the communication time for transmitting data from the inertial navigation system model to the flight attitude simulator, the time taken for the flight attitude simulator to actually move after receiving a control command, and the difference in processing delay between the actual hardware and the simulation model.

[0017] Furthermore, according to the present disclosure, communication delay times are compensated for for the guidance control system and actuator models, respectively, thereby enabling the precise simulation of the overall operation of a closed-loop system in which control commands are transmitted to the actuator and the response is fed back to the controller. This makes it possible to accurately predict the impact of minute delays on the stability, responsiveness, and precision of the aircraft.

[0018] Furthermore, according to the present disclosure, a high-fidelity simulation environment very similar to an actual flight environment can be established through such independent task configurations and sophisticated delay compensation mechanisms, even when physical hardware is not fully equipped. This enables pre-verification and prediction during the early stages of aircraft development, thereby significantly contributing to reducing development costs, shortening development time, and early detection and correction of design errors.

[0019] In addition, according to the present disclosure, delay factors occurring during the simulation process can be analyzed early from the design stage and reflected in the 6-degrees-of-freedom equations of motion and subsystem models. This improves the completeness of the aircraft design and minimizes the possibility of unexpected problems.

[0020] The effects according to the technical concept of the present disclosure are not limited to the effects mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art to which the present disclosure belongs from the description below. Brief explanation of the drawing

[0021] A brief description of each drawing is provided to help to better understand the drawings cited in the present disclosure. FIG. 1 is a block diagram showing the schematic configuration of an inertial sensor aircraft simulation system according to an exemplary embodiment of the present disclosure. FIG. 2 is a block diagram showing the detailed data flow and delay compensation mechanism of an inertial sensor aircraft simulation system according to an exemplary embodiment of the present disclosure. FIG. 3 is a flowchart illustrating an inertial sensor aircraft simulation method according to an exemplary embodiment of the present disclosure. FIG. 4 is a block diagram showing the detailed configuration of a coordinate system interconversion algorithm according to an exemplary embodiment of the present disclosure. FIG. 5 is a block diagram illustrating in detail the calculation and application process of a total inertial navigation system delay according to an exemplary embodiment of the present disclosure. FIG. 6 is a diagram conceptually illustrating the clock synchronization process of a plurality of independent tasks according to an exemplary embodiment of the present disclosure. FIG. 7 is a block diagram schematically showing the hardware configuration of a computing device constituting an inertial sensor aircraft simulation system according to an exemplary embodiment of the present disclosure. Specific details for implementing the invention

[0022] Exemplary embodiments according to the technical concept of the present disclosure are provided to more fully explain the technical concept of the present disclosure to those skilled in the art, and the following embodiments may be modified in various different forms, and the scope of the technical concept of the present disclosure is not limited to the following embodiments. Rather, these embodiments are provided to make the present disclosure more faithful and complete and to fully convey the technical concept of the present disclosure to those skilled in the art.

[0023] In this disclosure, terms such as "first," "second," etc. are used to describe various members, regions, layers, parts, and / or components; however, it is obvious that these members, parts, regions, layers, parts, and / or components should not be limited by these terms. These terms do not imply a specific order, hierarchy, or superiority, and are used solely to distinguish one member, region, part, or component from another. Accordingly, the first member, region, part, or component described below may refer to the second member, region, part, or component without departing from the teachings of the technical concept of this disclosure. For example, without departing from the scope of rights of this disclosure, the first component may be named the second component, and similarly, the second component may be named the first component.

[0024] Unless otherwise defined, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by those skilled in the art to which the concept of this disclosure belongs. Furthermore, commonly used terms, such as those defined in advance, should be interpreted as having a meaning consistent with what they mean in the context of the relevant technology, and should not be interpreted in an overly formal sense unless explicitly defined herein.

[0025] Where an embodiment can be implemented differently, a specific process sequence or sequence of steps may be performed differently from the order described. For example, two processes or steps described in succession may be performed substantially simultaneously or in the reverse order of the order described.

[0026] In addition, terms such as “~part,” “~device,” “~device,” and “~module” described in this specification refer to a unit that processes at least one function or operation, and may be implemented as hardware or software or a combination of hardware and software such as a processor, microprocessor, microcontroller, CPU (Central Processing Unit), AP (Application Processor), GPU (Graphics Processing Unit), NPU (Neural Processing Unit), APU (Accelerate Processor Unit), DSP (Drive Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), etc., and may also be implemented in a form combined with memory that stores data necessary for processing at least one function or operation.

[0027] Furthermore, it is intended to clarify that the classification of components in this specification is merely based on the primary function each component is responsible for. That is, two or more components described below may be combined into a single component, or a single component may be divided into two or more components based on more subdivided functions. Additionally, each component described below may additionally perform some or all of the functions of other components in addition to its primary function, and it is obvious that some of the primary functions of each component may be exclusively performed by other components.

[0028] The term 'and / or' as used herein includes each of the mentioned members and all combinations of one or more.

[0029] Hereinafter, embodiments according to the technical concept of the present disclosure will be described in detail with reference to the attached drawings.

[0030] FIG. 1 is a block diagram showing the schematic configuration of an inertial sensor aircraft simulation system according to an exemplary embodiment of the present disclosure.

[0031] Referring to FIG. 1, the inertial sensor aircraft simulation system according to the present invention may include a simulation control device (100) and a flight attitude simulator (FMS) (200).

[0032] The simulation control device (100) provides a core computing environment for performing a simulation to predict the closed-loop performance of an inertial sensor aircraft in advance. As an example of a configuration for this, the simulation control device (100) may include a processing unit (110) and a clock synchronization unit (140).

[0033] The processing unit (110) may include a plurality of processors that perform calculations necessary for the simulation, such as a first processor (120) and a second processor (130). These processors (120, 130) may each be configured to execute a plurality of independent tasks, such as a 6-degrees-of-freedom equation of motion model (122), a guidance control model (132), a driving model (126), and a navigation system model (136). Each independent task has a unique calculation cycle and can simulate the distributed processing environment and asynchronous operation characteristics of an actual aircraft system.

[0034] For example, the first processor (120) can execute a 6-degree-of-freedom equation of motion model (122) and a driving model (126), and the second processor (130) can execute a guidance control model (132) and a navigation system model (136).

[0035] These processors (120, 130) may include communication modules (124, 134) for data transmission between independent tasks. For example, the communication module (124) in the first processor (120) may be responsible for data exchange between a 6-degree-of-freedom equation of motion model (122) and a driving model (126), and the communication module (134) in the second processor (130) may be responsible for data exchange between a guidance control model (132) and a navigation system model (136). Additionally, the communication modules (124, 134) may enable data transmission between the first processor (120) and the second processor (130), thereby supporting communication between independent tasks assigned to different processors.

[0036] The clock synchronization unit (140) is located within the simulation control device (100) and can be configured to synchronize the operation cycles of each of the multiple independent tasks executed on the multiple processors (120, 130). The clock synchronization unit (140) distributes clock signals generated by the simulation control device to each independent task, thereby ensuring that each task performs operations and exchanges data in accordance with a common time standard, thereby ensuring the reliability and accuracy of the real-time simulation.

[0037] The flight attitude simulator (FMS) (200) is linked with the simulation control device (100) and can measure angular velocity values ​​in actual flight simulations or perform the role of physically moving according to the results of the 6-degrees-of-freedom equation of motion model. The simulation control device (100) can receive the measured angular velocity values ​​from the FMS (200) or transmit commands to drive the FMS (200).

[0038] FIG. 2 is a block diagram showing the detailed data flow and the interaction between components of an inertial sensor aircraft simulation system according to an exemplary embodiment of the present disclosure.

[0039] FIG. 2 shows in detail a plurality of independent tasks executed within the processing unit (110) of the simulation control device (100) illustrated in FIG. 1 and the data flow between them and the flight attitude simulator (FMS) (200).

[0040] The system illustrated in FIG. 2 may include a 6-degrees-of-freedom equation of motion model (122), a drive model (126), a guidance control model (132), a navigation system model (136), and a flight attitude simulator (FMS) (200).

[0041] The 6-degrees-of-freedom equation of motion model (122) corresponds to an independent task that calculates the dynamic movement of the aircraft. This model generates motion state information such as the position, velocity, attitude, and angular velocity of the aircraft, and can perform calculations by receiving control commands from the guidance control model (132) and responses from the driving model (126) as inputs. The angular velocity value derived from the 6-degrees-of-freedom equation of motion model (122) can be transmitted to the flight attitude simulator (FMS) (200) through the converter (1369) of the navigation system model (136).

[0042] The driving model (126) corresponds to an independent task that simulates the operation of the aircraft's driving device (actuator). This model can receive control commands from the guidance control model (132) and generate forces and torques applied to the 6-degrees-of-freedom equation of motion model (122).

[0043] The guidance control device model (132) corresponds to an independent task that simulates the control logic of the aircraft. This model receives navigation information generated from the navigation computer model (1367) of the navigation system model (136) and generates control commands for guiding the flight path and attitude of the aircraft, and the generated control commands can be transmitted to the driving model (126).

[0044] The navigation system model (136) corresponds to an independent task that calculates and manages navigation information of the aircraft. For example, the navigation system model (136) may include a satellite navigation model (1361), an angular velocity sensor model (1363), an acceleration sensor model (1365), a navigation computer model (1367), and a transducer (1369).

[0045] The satellite navigation model (1361) corresponds to an independent task that simulates position and velocity data from a satellite navigation system (GPS, etc.).

[0046] The angular velocity sensor model (1363) corresponds to an independent task that simulates the angular velocity value that can be measured by the angular velocity sensor of the aircraft. The angular velocity sensor model (1363) receives the angular velocity value from the 6-degree-of-freedom equation of motion model (122), generates virtual sensor data, and can transmit it to the navigation computer model (1367). As described later in FIG. 3, the angular velocity value transmitted to the navigation computer model (1367) can be provided from the angular velocity sensor model (1363) or the FMS (200).

[0047] The acceleration sensor model (1365) corresponds to an independent task that simulates acceleration values ​​that can be measured by the acceleration sensor of the aircraft. The acceleration sensor model (1365) receives acceleration values ​​from the 6-degree-of-freedom equation of motion model (122), generates virtual sensor data, and can transmit it to the navigation computer model (1367).

[0048] The navigation computer model (1367) is an independent task that receives data from the satellite navigation model (1361), the angular velocity sensor model (1363), the acceleration sensor model (1365), and / or the transducer (1369) and performs navigation calculations such as the current position, velocity, and attitude of the aircraft. The output of this model can be transmitted to the guidance control model (132).

[0049] The converter (1369) corresponds to an independent task that executes a coordinate system interconversion algorithm to resolve discrepancies caused by different coordinate systems when exchanging data between the 6-degrees-of-freedom equations of motion model (122) or the navigation computer model (1367) and the flight attitude simulator (FMS) (200). The angular velocity value derived from the 6-degrees-of-freedom equations of motion model (122) is transmitted to the FMS (200) through the converter (1369), and the angular velocity value measured from the FMS (200) can be transmitted to the navigation computer model (1367) via the converter (1369).

[0050] The flight attitude simulator (FMS) (200) is an external physical device connected to the simulation control device (100). The FMS (200) actually moves according to the angular velocity command transmitted through the transducer (1369) from the result of the 6-degree-of-freedom equation of motion model (122), and can feed back the angular velocity value measured through the sensor (e.g., IMU) mounted inside the FMS to the navigation computer model (1367) via the transducer (1369).

[0051] FIG. 3 is a flowchart illustrating an inertial sensor aircraft simulation method according to an exemplary embodiment of the present disclosure. FIG. 4 is a block diagram illustrating the detailed configuration of a coordinate system interconversion algorithm according to an exemplary embodiment of the present disclosure. FIG. 5 is a block diagram illustrating in detail the calculation and application process of a total inertial navigation system delay according to an exemplary embodiment of the present disclosure.

[0052] The flowchart of FIG. 3 illustrates the main steps performed in the processing unit (110) of the simulation control device (100).

[0053] Referring to FIG. 3, the simulation method may include the following steps.

[0054] First, the simulation control device (100) can acquire the simulation initial position information of the aircraft to be simulated and the physical position information of the FMS (200), and operate a plurality of independent tasks (S310).

[0055] This step may include initializing and preparing for execution of a plurality of independent tasks, such as a 6-degrees-of-freedom equation of motion model (122), a navigation system model (136) (including the navigation computer model (1367) of FIG. 2), a guidance control model (132), and a driving model (126). In this process, the operation cycle of each independent task is synchronized through a clock generated by a clock synchronization unit (140) within the simulation control unit (100), so that the simulation can proceed on a consistent time basis.

[0056] Next, the simulation control device (100) can check whether it is in the angular velocity measurement mode through the FMS (S315).

[0057] For example, the simulation control device (100) can determine, based on input from a user (or manager), whether the simulation environment is in a mode that measures angular velocity values ​​using a flight attitude simulator (FMS) (200) or in a mode that calculates angular velocity values ​​through an angular velocity sensor model (1363).

[0058] If the result of the check is that the angular velocity measurement mode is through the FMS (YES of S315), the simulation control device (100) can transmit the angular velocity derived from the 6-degree-of-freedom equation of motion model (122) to the FMS (200) through the converter (1369) (S320).

[0059] This step may include executing a coordinate system interconversion algorithm in a converter (1369) to convert the angular velocity values ​​of the coordinate system used in the 6-degree-of-freedom equation of motion model (122) to match the coordinate system of the FMS (200).

[0060] The simulation control device (100) receives the angular velocity value measured through the FMS (200) and can provide the received angular velocity value to the navigation computer model (1367) (S325).

[0061] The angular velocity value measured in the FMS (200) corresponds to data according to the coordinate system of the FMS (200). Accordingly, the converter (1369) executes a coordinate system interconversion algorithm that converts the angular velocity value to the coordinate system used by the navigation computer model (1367), and can transmit the converted data to the navigation computer model (1367) according to the result of the execution.

[0062] Referring to FIG. 4 in relation to steps S320 to S325, the converter (1369) can execute an algorithm to mutually convert the coordinate systems of the data when exchanging data between one or more of the flight attitude simulator (FMS) (200) and the inertial navigation system (INS) model (136) or the 6-degrees-of-freedom equations of motion model (122), if the coordinate system used in the FMS (200) is different from the coordinate system used in the other model.

[0063] For example, if the Euler angle needs to be converted to fit the gimbal structure of the FMS (200), the converter (1369) can express the relationship between the angular velocity values ​​(Pb, Qb, Rb) and the Euler angles (Θ, Ψ, Φ) through matrix operations such as Equations 1 and 2 below, and calculate the Euler angular velocity as in Equation 3.

[0064]

[0065]

[0066]

[0067] Through this conversion operation, the converter (1369) can convert the angular velocity value measured in the FMS (200) into a coordinate system used by the navigation system model (136), or convert the angular velocity value derived from the 6-degree-of-freedom equation of motion model (122) into a coordinate system for driving the FMS (200).

[0068] On the other hand, if the result of the verification in step S315 corresponds to an angular velocity calculation mode through an angular velocity sensor model (NO of S315), the simulation control device (100) can calculate the angular velocity value (S330) through the angular velocity sensor model (1363). In this case, since the FMS (200) is not used, coordinate system transformation related to the FMS (200) may not occur.

[0069] The calculated angular velocity value can be provided to the navigation computer model (1367) (S335). The angular velocity value calculated in the angular velocity sensor model (1363) can be used as an input to the navigation computer model (1367).

[0070] Subsequently, data transfer between independent tasks (S340) may be performed. This step includes exchanging necessary data between multiple independent tasks (models), and data transfer may be performed, for example, using an asynchronous shared memory (e.g., VME (VERSA Module Eurocard) shared memory) within a communication module (124, 134 in FIG. 1). By using an asynchronous VME shared memory, communication delay time between processors may be minimized.

[0071] Next, delay compensation steps to increase the accuracy of the simulation can be performed sequentially.

[0072] Referring to FIG. 3 and FIG. 5 together, the simulation control device (100) has a total inertial navigation system delay (T INS ) can be calculated and applied to the data transmission cycle (S345).

[0073] At this stage, the processing unit (110) is the communication time (TC) from the navigation system model (136) to the FMS (200). INStoFMS ), physical response time (TP) of FMS (200) FmsFeedback ), and the difference in processing latency between actual hardware and the simulation model (T offsetTotal inertial navigation system delay (T) including ) INS ) can be calculated (refer to mathematical formula 4 below).

[0074]

[0075] The processing unit (110) calculates the total inertial navigation system delay (T INS Communication delay can be handled by compensating for the data transmission cycle between the navigation system model (136) and the FMS (200).

[0076] The simulation control device (100) can apply the guidance control device delay to the data transmission cycle of the guidance control device model (132) (S350).

[0077] For example, the processing unit (110) may set a preset guidance control delay value as a delay for the guidance control model (132) to compensate for the average communication time that may occur in a flight environment. The processing unit (110) may process the communication delay by compensating the set delay for the data transmission period between the guidance control model (132) and the 6-degree-of-freedom equation of motion model (122).

[0078] The simulation control device (100) can apply a driving model delay to the data transmission cycle of the driving model (126) (S355).

[0079] For example, the processing unit (110) may set a preset driving device delay value as a delay for the driving model (126) to compensate for the average communication time that may occur in a flight environment. The processing unit (110) may process the communication delay by compensating the set delay for the data transmission period between the driving model (126) and the 6-degree-of-freedom equation of motion model (122).

[0080] Although not explicitly stated, after step S355, the simulation control unit (100) may proceed to a step of determining the conditions for terminating the simulation. If the simulation termination conditions are not met, the simulation may be repeated by returning to an appropriate simulation cycle starting point, such as step S310 or step S315. If the simulation termination conditions are met, the simulation may be terminated. Through this iterative execution, the simulation control unit (100) can simulate continuous changes in the actual flight environment and predict closed-loop performance.

[0081] FIG. 6 is a diagram conceptually illustrating the clock synchronization process of a plurality of independent tasks according to an exemplary embodiment of the present disclosure.

[0082] Referring to FIG. 6, the simulation control device (100) may include a clock generation unit (610) and a clock synchronization unit (140). The clock generation unit (610) may perform the role of generating a master clock signal of the simulation control device (100). This master clock signal may be transmitted to the clock synchronization unit (140).

[0083] The clock synchronization unit (140) receives a master clock signal from the clock generation unit (610) and can perform the function of synchronizing the operation cycles of each of the multiple independent tasks, namely the navigation system model (136), the guidance control device model (132), and the driving model (126), based on this clock signal.

[0084] When considering the operations performed in each independent task (navigation system model (136), guidance control model (132), drive model (126)) prior to clock synchronization, each independent task performs operations according to a unique operation cycle, while the start time and duration of their operations may differ. This is due to the asynchronous nature of each task operating independently of one another. Such asynchronous and unaligned operation cycles and data exchange timings make it difficult to accurately simulate the distributed processing and asynchronous operation characteristics of an actual flight environment, and consequently, may cause problems where the simulation results differ significantly from actual flight data.

[0085] On the other hand, according to the present disclosure, the operation cycle of each independent task can be aligned with the synchronization clock signal distributed by the clock synchronization unit (140). This means that each task can operate by starting the operation in accordance with a common clock tick, or by completing the operation and preparing data within a specific clock tick. Even in this case, the actual operation period of each task may be maintained differently depending on its unique complexity, but it can be confirmed that the operation cycle itself can be consistently synchronized with the clock signal.

[0086] Through this clock synchronization process, multiple independent tasks can perform calculations and exchange data according to a predictable and consistent time flow within the simulation control device (100). This can contribute to ensuring the reliability and accuracy of the simulation and guaranteeing that the timing of data exchange between independent tasks does not deviate.

[0087] FIG. 7 is a block diagram schematically showing the hardware configuration of a computing device constituting an inertial sensor aircraft simulation system according to an exemplary embodiment of the present disclosure.

[0088] Referring to FIG. 7, the computing device (700) may include a communication unit (710), an input unit (720), an output unit (730), a control unit (740), and a memory (750). The control configuration shown in FIG. 7 is an example for convenience of explanation, and the computing device (700) may include more or fewer configurations than the configuration shown in FIG. 7.

[0089] The communication unit (710) may include one or more communication modules that enable communication with other computing devices or servers, etc., by connecting the computing device (700) to a network. For example, the communication module may include a mobile communication module such as LTE, 5G, etc., a wireless communication module such as Wi-Fi, etc., and / or various other wired or wireless communication modules.

[0090] The input unit (720) is configured to acquire information such as user input, video, and audio, and may include various input means such as various mechanical / electronic input means, cameras, and microphones. The output unit (730) is configured to provide information to a user by generating output related to sight, hearing, or touch, and may include a display, speakers, and vibration modules.

[0091] The control unit (740) can control the overall operation of the computing device (700). The control unit (740) can process signals, data, information, etc. that are input or output through the components described above, or provide certain information or functions according to various applications or algorithms stored in the memory (750). For example, the control unit (740) can correspond to the processing unit (110) of FIG. 1.

[0092] The control unit (740) may include at least one processor and / or at least one programmable circuit. For example, the control unit (740) may be implemented in hardware such as a CPU, an application processor (AP), an MCU, a GPU, an NPU, an integrated circuit, an ASIC, an FPGA, etc.

[0093] The memory (750) can store programs and data necessary for the operation of the computing device (700). Additionally, the memory (750) can store data generated or acquired through the control unit (740). The memory (750) may be composed of a storage medium such as ROM, RAM, flash memory, SSD, HDD, or a combination of storage media.

[0094] The embodiments of the present disclosure described above can be implemented as computer-readable code on a medium on which a program is recorded. Computer-readable media include all types of recording devices in which data that can be read by a computer system is stored. Examples of computer-readable media include HDD (Hard Disk Drive), SSD (Solid State Disk), SSD (Silicon Disk Drive), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

[0095] The description of the above-described embodiments is merely an example provided with reference to the drawings for a more thorough understanding of the present disclosure, and should not be interpreted as limiting the technical scope of the present disclosure.

[0096] Furthermore, it will be apparent to those skilled in the art to which this disclosure pertains that various changes and modifications are possible within the scope of the basic principles of this disclosure.

Claims

Claim 1 An inertial sensor aircraft simulation system comprising at least one computing device, comprising: a plurality of independent tasks, each having a computational cycle, each executing one of a 6-degrees-of-freedom equations of motion model, an Inertial Navigation System (INS) model, a Guidance / Control Unit (GCU) model, and an actuator model; a communication module for data transmission between the plurality of independent tasks; and a clock synchronization device configured to distribute clock signals to the plurality of independent tasks to synchronize the computational cycles of the plurality of independent tasks so that the plurality of independent tasks perform computations and exchange data in accordance with a common time reference. An inertial sensor flight vehicle simulation system comprising a processing unit configured to manage the execution of the plurality of independent tasks, calculate a total inertial navigation system delay including the communication time from the INS model to the Flight Motion Simulator (FMS), the physical response time of the FMS, and the difference in processing delay between the actual hardware and the simulation model, calculate a guidance control delay for the GCU model, calculate a actuator delay for the actuator model, and process communication delays by compensating the total inertial navigation system delay, the guidance control delay, and the actuator delay for each delay in a data transmission period corresponding to each delay. Claim 2 An inertial sensor flight vehicle simulation system according to claim 1, wherein the communication module is configured to perform data transmission between the plurality of independent tasks using asynchronous shared memory. Claim 3 In paragraph 2, the asynchronous shared memory comprises a VME (VERSA Module Eurocard) shared memory, in an inertial sensor aircraft simulation system. Claim 4 In claim 1, the processing device is optionally configured to measure an angular velocity value through the FMS or to calculate an angular velocity value through an angular velocity sensor model, in an inertial sensor flight vehicle simulation system. Claim 5 An inertial sensor aircraft simulation system according to claim 4, wherein the processing device is configured to execute a transformation algorithm for mutually transforming the coordinate systems of the data when the coordinate system used in the FMS and the coordinate system used in the other model are different when the processing device measures an angular velocity value through the FMS and exchanges data between the FMS and one or more of the INS model or the 6-degrees-of-freedom equation of motion model. Claim 6 In claim 5, the above conversion algorithm includes an operation to convert Euler angular velocity into Euler angle, in an inertial sensor aircraft simulation system. Claim 7 delete Claim 8 An inertial sensor aircraft simulation system according to claim 1, wherein the processing device is configured to transmit an angular velocity value derived from the 6-degrees-of-freedom equation of motion model to the FMS through a converter, and to receive the angular velocity value from the FMS in the INS model to perform navigation calculations. Claim 9 An inertial sensor flight vehicle simulation system according to claim 1, wherein the processing device is configured to handle the communication delay between the INS model and the FMS by compensating the calculated total INS delay to the data transmission period of the INS model. Claim 10 An inertial sensor aircraft simulation system according to claim 1, wherein the processing device is configured to process the communication delay between the GCU model and the 6-degrees-of-freedom equation of motion model by compensating the calculated guidance control device delay for the data transmission period of the GCU model. Claim 11 An inertial sensor flight vehicle simulation system according to claim 1, wherein the processing device is configured to process the communication delay between the driving device model and the 6-degrees-of-freedom equation of motion model by compensating the calculated driving device delay for the data transmission period of the driving device model. Claim 12 A simulation method for pre-predicting the closed-loop performance of an inertial sensor aircraft comprises: a step of executing one of a 6-degrees-of-freedom equations of motion model, an Inertial Navigation System (INS) model, a Guidance / Control Unit (GCU) model, and an actuator model, and operating a plurality of independent tasks each having a respective computation cycle; a step of transmitting data between the plurality of independent tasks; a step of synchronizing the respective computation cycles of the plurality of independent tasks by distributing clock signals to the plurality of independent tasks so that the plurality of independent tasks perform computations and exchange data according to a common time reference; a step of calculating a total Inertial Navigation System (INS) delay including the communication time from the INS model to a Flight Motion Simulator (FMS), the physical response time of the FMS, and the difference in processing delay between actual hardware and the simulation model; a step of calculating the Guidance / Control Unit delay for the GCU model; and a step of calculating the actuator delay for the actuator model. A simulation method comprising the step of processing communication delays by compensating the total inertial navigation system delay, the guidance control device delay, and the actuator delay, respectively, for each delay in a data transmission period corresponding to each delay. Claim 13 In claim 12, the step of transmitting the data includes the step of transmitting data between the plurality of independent tasks using asynchronous shared memory, a simulation method. Claim 14 In claim 12, the step of transmitting the data includes, when measuring an angular velocity value through the FMS, when exchanging data between the FMS and one or more of the INS model or the 6-degrees-of-freedom equation of motion model, when the coordinate system used in the FMS and the coordinate system used in the other model are different, a simulation method. Claim 15 In claim 12, the step of operating the plurality of independent tasks comprises the step of transmitting an angular velocity value derived from the 6-degree-of-freedom equation of motion model to the FMS through a converter, and receiving the angular velocity value from the FMS in the INS model to perform navigation calculations, a simulation method.

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