Navigation equipment fault detection method and device, equipment, carrier and storage medium

Abstract

The embodiment of the invention provides a navigation equipment fault detection method and device, equipment, a carrier and a storage medium, and the method comprises the steps: determining whether a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware exist in all IMUs according to the detection data of every two IMUs belonging to different integrated navigation equipment; under the condition that at least two normal IMUs exist, according to the INS resolving results of every two normal IMUs, determining whether a second abnormal IMU with software exception exists in all the normal IMUs or not; determining whether an abnormal GNSS navigation module exists in all the GNSS navigation modules or not according to the GNSS resolving results of every two GNSS navigation modules belonging to different integrated navigation devices; and under the condition that at least one abnormal device in the first abnormal IMU, the second abnormal IMU or the abnormal GNSS navigation module exists, reporting the abnormal device to a control module of the carrier.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a navigation device fault detection method, device, equipment, carrier and storage medium. Background Art

[0002] Navigation equipment is widely used in the fields of navigation, aviation, astronomy, hydrology and land transportation, and is used to provide information such as heading and position for the carrier on which it is mounted, so as to ensure the safe operation of the carrier. Therefore, navigation equipment is particularly important for the safe operation of the carrier, especially the aircraft, because the failure of the navigation equipment can easily cause problems in the flight of the aircraft, or even cause the aircraft to crash.

[0003] The navigation equipment of an aircraft generally includes an inertial navigation module and a GNSS navigation module. The inertial navigation module is usually an inertial measurement unit (IMU), which is prone to failure due to its own hardware or software reasons, while the GNSS signal received by the GNSS navigation module is easily interfered by the external environment or affected by spoofed signals, resulting in errors. In this way, if at least one of the inertial navigation module or the GNSS navigation module fails, if the aircraft continues to use the fault information, it will obviously seriously threaten the flight safety of the aircraft. Summary of the invention

[0004] In view of this, in order to at least solve the technical problem in the related art that the aircraft is unable to know whether the navigation equipment has a fault and continues to use the fault information collected by the faulty navigation equipment, which affects the flight safety, the purpose of the present invention is to provide a navigation equipment fault detection method, device, equipment, carrier and storage medium.

[0005] In order to achieve the above purpose, the technical solution adopted by the embodiment of the present invention is as follows:

[0006] According to a first aspect of an embodiment of the present invention, a navigation device fault detection method is provided, which is used to perform fault detection on a plurality of integrated navigation devices installed on a carrier, each of which includes an IMU and a GNSS navigation module; the method includes:

[0007] Determine, according to detection data of every two IMUs belonging to different integrated navigation devices, whether there is a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware among all the IMUs;

[0008] In the case where there are at least two normal IMUs, determining whether there is a second abnormal IMU with software abnormality among all the normal IMUs according to the INS solution results of every two normal IMUs;

[0009] Determine whether there is an abnormal GNSS navigation module among all the GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different integrated navigation devices;

[0010] In the case that at least one abnormal device among the first abnormal IMU, the second abnormal IMU, or the abnormal GNSS navigation module exists, the abnormal device is reported to the control module of the carrier.

[0011] In an optional implementation, each integrated navigation device is configured with a Kalman filter and a state monitoring filter; before reporting the abnormal device to the control module of the carrier, the method further includes:

[0012] For each integrated navigation device, outputting a corresponding current estimated state matrix through a Kalman filter in the integrated navigation device based on a current INS solution result and a current GNSS solution result respectively outputted by an IMU and a GNSS navigation module in the integrated navigation device at a current moment; the current estimated state matrix includes an estimated speed, an estimated position, and an estimated attitude;

[0013] For each integrated navigation device, outputting a corresponding current observation state matrix based on a current INS solution result output by an IMU in the integrated navigation device at the current moment through a state monitoring filter in the integrated navigation device; the current observation state matrix includes an observation speed, an observation position and an observation attitude;

[0014] For each integrated navigation device, a current state error matrix is ​​calculated based on the corresponding current estimated state matrix and the current observed state matrix; the current state error matrix includes the error between the corresponding estimated speed and the observed speed, the error between the corresponding estimated position and the observed position, and the error between the corresponding estimated attitude and the observed attitude;

[0015] For each integrated navigation device, a fault detection value of the integrated navigation device is calculated according to the corresponding current state error matrix;

[0016] Obtaining a fault detection result of each integrated navigation device according to the fault detection value of each integrated navigation device and a preset fault threshold value; the fault detection result includes a normal result indicating that the integrated navigation device is normal, or an abnormal result indicating that the integrated navigation device is abnormal;

[0017] According to the fault detection result of the integrated navigation device, determining a target abnormal device from the determined abnormal devices;

[0018] Correspondingly, the step of reporting the abnormal device to the control module of the carrier is adjusted to: in the case where the target abnormal device exists, reporting the target abnormal device to the control module of the carrier.

[0019] In an optional embodiment, the state monitoring filter is configured with two; the step of outputting the corresponding current observation state matrix through the state monitoring filter in the integrated navigation device based on the current INS solution result output by the IMU in the integrated navigation device at the current moment comprises:

[0020] When the monitoring time of the currently selected current state monitoring filter does not reach half of the set monitoring period, the observation state matrix output by the current state monitoring filter based on the current INS solution result is discarded;

[0021] When the monitoring duration of the current state monitoring filter reaches half of the set monitoring period, the observation state matrix output by the current state monitoring filter based on the current INS solution result is used as the current observation state matrix, and another state monitoring filter is initialized; wherein the monitoring duration of the initialized another state monitoring filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at the time of its initialization;

[0022] When the monitoring duration of the current state monitoring filter reaches the set monitoring period, the current state monitoring rate filter is initialized, and the other state monitoring filter is used as the current state monitoring filter; wherein the monitoring duration of the initialized current state monitoring rate filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at its initialization time.

[0023] In an optional embodiment, the state monitoring filter is configured with only one; the step of outputting the corresponding current observation state matrix through the state monitoring filter in the integrated navigation device based on the current INS solution result output by the IMU in the integrated navigation device at the current moment comprises:

[0024] When the monitoring time of the state monitoring filter does not reach half of the set monitoring period, discarding the observation state matrix output by the state monitoring filter based on the current INS solution result;

[0025] When the monitoring time of the state monitoring filter reaches half of the set monitoring period, the observation state matrix output by the state monitoring filter based on the current INS solution result is used as the current observation state matrix;

[0026] When the monitoring duration of the state monitoring filter reaches the set monitoring period, the state monitoring filter is initialized; wherein, the monitoring duration of the initialized state monitoring filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at its initialization time.

[0027] In an optional implementation manner, the step of determining a target abnormal device from the determined abnormal devices according to the fault detection result of the integrated navigation device includes:

[0028] For each abnormal component, if the fault detection result of the combined navigation device to which the abnormal component belongs is a normal result, the fault detection result of the abnormal component is updated to normal; if the fault detection result of the combined navigation device to which the abnormal component belongs is an abnormal result, the abnormal component is determined as a target abnormal component.

[0029] In an optional embodiment, the method further comprises:

[0030] For each normal component that has been determined, if the fault detection result of the combined navigation device to which the normal component belongs is a normal result, or if the fault detection result of the combined navigation device to which the normal component belongs is an abnormal result and another component in the combined navigation device to which the normal component belongs is an abnormal component that has been determined, then the normal component is determined to be normal; if the fault detection result of the combined navigation device to which the normal component belongs is an abnormal result and another component in the combined navigation device to which the normal component belongs is not an abnormal component that has been determined, then the normal component and the other component in the combined navigation device to which the normal component belongs are determined as target abnormal components.

[0031] In an optional embodiment, the detection data includes acceleration and angular velocity; the step of determining a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware according to the detection data of each two IMUs belonging to different combined navigation devices comprises:

[0032] According to the acceleration deviation between the accelerations detected by every two IMUs and the set acceleration deviation threshold, and the angular velocity deviation between the angular velocities detected by every two IMUs and the set angular velocity deviation threshold, the normal IMU and the first abnormal IMU are obtained;

[0033] Among them, the acceleration deviation and angular velocity deviation between the normal IMU and the normal IMU are both smaller than their corresponding deviation thresholds, and at least one of the acceleration deviation or angular velocity deviation between the first abnormal IMU and any IMU is not smaller than the corresponding deviation threshold.

[0034] In an optional embodiment, the INS solution result includes position information, attitude information and speed; the step of determining whether there is a second abnormal IMU with software abnormality among all normal IMUs according to the INS solution results of every two normal IMUs includes:

[0035] Determine whether there is the second abnormal IMU according to the position deviation between the position information and the set position deviation threshold, the attitude deviation between the attitude information and the set attitude deviation threshold, and the speed deviation between the speeds and the set speed deviation threshold in the INS solution results of each two normal IMUs;

[0036] Among them, at least one of the position deviation, attitude deviation or speed deviation between the second abnormal IMU and any IMU is not less than the corresponding deviation threshold.

[0037] In an optional implementation, the GNSS solution result includes position information, attitude information and speed; the step of determining whether there is an abnormal GNSS navigation module among all GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different combined navigation devices comprises:

[0038] Determine whether there is an abnormal GNSS navigation module according to the position deviation between the position information and the set position deviation threshold, the attitude deviation between the attitude information and the set attitude deviation threshold, and the speed deviation between the speeds and the set speed deviation threshold in the GNSS solution results of every two GNSS navigation modules;

[0039] Wherein, at least one of the position deviation, attitude deviation or speed deviation between the abnormal GNSS navigation module and any GNSS navigation module is not less than the corresponding deviation threshold.

[0040] According to a second aspect of an embodiment of the present invention, there is provided a navigation device fault detection apparatus for performing fault detection on a plurality of combined navigation devices installed on a carrier, each of the combined navigation devices comprising an IMU and a GNSS navigation module; the apparatus comprises:

[0041] The hard fault determination module is configured to: determine whether there is a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware among all the IMUs according to the detection data of every two IMUs belonging to different combined navigation devices;

[0042] The soft fault determination module is configured to: when there are at least two normal IMUs, determine whether there is a second abnormal IMU with software abnormality among all the normal IMUs according to the INS solution results of every two normal IMUs;

[0043] The GNSS fault determination module is configured to: determine whether there is an abnormal GNSS navigation module among all the GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different combined navigation devices;

[0044] The reporting module is configured to: in the event that at least one abnormal device among the first abnormal IMU, the second abnormal IMU, or the abnormal GNSS navigation module exists, report the abnormal device to the control module of the carrier.

[0045] According to a third aspect of an embodiment of the present invention, an electronic device is provided, comprising a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor can execute the machine executable instructions to implement the navigation device fault detection method provided in the first aspect above.

[0046] A fourth aspect of the embodiments of the present invention provides a carrier, including:

[0047] Body;

[0048] A plurality of combined navigation devices are respectively installed at different parts of the aircraft body;

[0049] A control module, used for controlling the operation of the body according to the outputs of the plurality of combined navigation devices;

[0050] The fault detection module is used to execute the navigation device fault detection method provided in the first aspect above, so as to determine whether there are abnormal components in the multiple combined navigation devices based on the outputs of the multiple combined navigation devices, and report to the control module if there are abnormal components.

[0051] According to a fifth aspect of an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the navigation device fault detection method provided in the first aspect is implemented.

[0052] The navigation device fault detection method, device, equipment, carrier and storage medium provided by the embodiment of the present invention first processes the detection data of each two IMUs belonging to different combined navigation devices to determine whether there is a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware. In the case of at least two normal IMUs, the INS solution results of each two normal IMUs are used to determine whether there is a second abnormal IMU with abnormal software among all normal IMUs. This can realize the fault detection of IMUs with abnormal hardware and abnormal software, and avoid only detecting the IMU with abnormal hardware, while ignoring the problem of low safety of carrier movement caused by the IMU with abnormal software. In addition, by also determining whether there is an abnormal GNSS navigation module according to the GNSS solution results of each two GNSS navigation modules belonging to different combined navigation devices, the fault detection of the abnormal GNSS navigation module can also be realized. Then, in the case of the presence of at least one abnormal device in the first abnormal IMU, the second abnormal IMU, or the abnormal GNSS navigation module, the abnormal device is reported to the control module of the carrier, so that the control module can change the control decision according to the abnormal device, for example, not using the data output by the abnormal device, but using the data output by the normal device, so as to improve the safety and reliability of movement.

[0053] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 A structural block diagram of an electronic device provided by an embodiment of the present invention is shown;

[0056] Figure 2 A flowchart of a navigation device fault detection method provided by an embodiment of the present invention is shown;

[0057] Figure 3 A functional module diagram of a navigation device fault detection apparatus provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0058] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0059] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0060] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0061] In order to solve the technical problem in the related art that the aircraft fails to know whether the navigation device has a fault and continues to use the fault information collected by the faulty navigation device, which affects the flight safety, an embodiment of the present invention provides a navigation device fault detection method, which first processes the detection data of each two IMUs belonging to different combined navigation devices to determine whether there is a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware. In the case of at least two normal IMUs, the INS solution results of each two normal IMUs are used to determine whether there is a second abnormal IMU with abnormal software among all normal IMUs, thereby realizing the fault detection of IMUs with abnormal hardware and abnormal software, avoiding the problem of low carrier movement safety caused by only detecting the IMU with abnormal hardware and ignoring the IMU with abnormal software. In addition, by also determining whether there is an abnormal GNSS navigation module based on the GNSS solution results of each two GNSS navigation modules belonging to different combined navigation devices, the fault detection of the abnormal GNSS navigation module can also be realized. Next, in the event of the presence of at least one abnormal device in the first abnormal IMU, the second abnormal IMU, or the abnormal GNSS navigation module, the abnormal device is reported to the control module of the carrier, so that the control module can change the control decision according to the abnormal device, for example, instead of using the data output by the abnormal device, the data output by the normal device is used to improve the safety and reliability of movement.

[0062] The navigation device fault detection method provided by the present invention can be applied to electronic devices, please refer to Figure 1 , is a block diagram of the structure of an electronic device. The electronic device 100 includes a memory 110, a processor 120 and a communication module 130. The memory 110, the processor 120 and the communication module 130 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0063] The memory is used to store programs or data. The memory may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0064] The processor is used to read / write data or programs stored in the memory and execute corresponding functions.

[0065] The communication module is used to establish a communication connection between the electronic device and other communication terminals through a network, and is used to send and receive data through the network.

[0066] It should be understood that Figure 1 The structure shown is only a schematic diagram of the structure of the electronic device, and the electronic device may also include Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown. Figure 1 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0067] In some embodiments, the electronic device can be configured in a carrier, and can obtain detection data, INS solution results and GNSS solution results of multiple integrated navigation devices on the carrier, and implement fault detection of multiple integrated navigation devices based on these data. The carrier can be an aircraft or a car, but is not limited to this. Each integrated navigation device includes an IMU and a GNSS navigation module.

[0068] The following combination Figure 2 The navigation device fault detection method provided by the embodiment of the present invention is described. Figure 2 : is a flowchart of a navigation device fault detection method provided by an embodiment of the present invention, the navigation device fault detection method comprising:

[0069] In step S100, based on the detection data of every two IMUs belonging to different integrated navigation devices, it is determined whether there is a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware among all the IMUs;

[0070] In step S200, when there are at least two normal IMUs, it is determined whether there is a second abnormal IMU with software abnormality among all the normal IMUs according to the INS solution results of every two normal IMUs;

[0071] In step S300, it is determined whether there is an abnormal GNSS navigation module among all the GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different integrated navigation devices;

[0072] In step S500, when there is at least one abnormal device among the first abnormal IMU, the second abnormal IMU, or the abnormal GNSS navigation module, the abnormal device is reported to the control module of the carrier.

[0073] In order to avoid the situation where there are abnormal devices in multiple combined navigation devices, the carrier still uses the data output by the abnormal devices, which leads to reduced safety and reliability of the carrier movement, especially for aircraft-type carriers, the reduced safety and reliability may cause the aircraft to explode, the above steps S100 to S500 in the navigation device fault detection method provided by the embodiment of the present invention can be performed during the movement of the carrier. The method can be executed by the control module, or by a fault detection module that is connected to the control module in communication, but is not limited to this, as long as the control module can be able to promptly know whether there are abnormal devices in all combined navigation devices, and which abnormal devices are there if there are abnormal devices.

[0074] In the process of executing step S100, the IMU may be firstly subjected to homology detection, that is, the detection data of every two IMUs belonging to different combined navigation devices may be processed to determine whether there are normal IMUs with normal hardware and first abnormal IMUs with abnormal hardware among all IMUs. In this regard, in some embodiments, in order to improve the acquisition efficiency of normal IMUs and first abnormal IMUs, the navigation device fault detection method provided by the embodiment of the present invention provides a way to implement step S100, that is, the detection data includes acceleration and angular velocity; accordingly, in the above step S100, the step of determining the normal IMUs with normal hardware and the first abnormal IMUs with abnormal hardware according to the detection data of every two IMUs belonging to different combined navigation devices may include:

[0075] In step S110, the normal IMU and the first abnormal IMU are obtained according to the acceleration deviation between the accelerations detected by every two IMUs and the set acceleration deviation threshold, and the angular velocity deviation between the angular velocities detected by every two IMUs and the set angular velocity deviation threshold.

[0076] Among them, the acceleration deviation and angular velocity deviation between the normal IMU and the normal IMU are both smaller than their corresponding deviation thresholds, and at least one of the acceleration deviation or angular velocity deviation between the first abnormal IMU and any IMU is not smaller than the corresponding deviation threshold.

[0077] For example, assuming that there are three integrated navigation devices, each of which includes an IMU, there are three IMUs, which are set as A1, A2 and A3 respectively. The acceleration detected by A1 is a1 and the angular velocity is w1; the acceleration detected by A2 is a2 and the angular velocity is w2; the acceleration detected by A3 is a3 and the angular velocity is w3; the acceleration deviation threshold is a0 and the angular velocity deviation threshold is w0. Based on this, in the process of executing step S110, the acceleration deviation and angular velocity deviation of each two IMUs can be calculated first: the acceleration deviation and angular velocity deviation of A1 and A2 are |a1-a2| and |w1-w2| respectively; the acceleration deviation and angular velocity deviation of A1 and A3 are |a1-a3| and |w1-w3| respectively; the acceleration deviation and angular velocity deviation of A2 and A3 are |a3-a2| and |w3-w2| respectively.

[0078] Next, |a1-a2|, |a1-a3|, and |a3-a2| are compared with a0, respectively, and |w1-w2|, |w1-w3|, and |w3-w2| are compared with w0, respectively.

[0079] If |a1-a2|<a0, |a1-a3|<a0, |a3-a2|<a0, |w1-w2|<w0, |w1-w3|<w0, and |w3-w2|<w0, it means that there is no first abnormal IMU with hardware abnormality. On the contrary, it means that there is a first abnormal IMU with hardware abnormality. Based on this, the comparison results can be used to infer which IMU device is abnormal. For example, if |a1-a2|<a0, |w1-w2|<w0, |a1-a3|≥a0, |w1-w3|≥w0, |a3-a2|≥a0 and |w3-w2|≥w0, it means that A1 and A2 are both normal IMUs with normal hardware, and A3 is the first abnormal IMU. That is to say, the acceleration deviation and angular velocity deviation between the normal IMU and the normal IMU are both less than their corresponding deviation thresholds, and at least one of the acceleration deviation or angular velocity deviation between the first abnormal IMU and any IMU is not less than the corresponding deviation threshold. Therefore, in the case of the presence of the first abnormal IMU, this principle can be used to determine which IMU is the first abnormal IMU.

[0080] In addition, if it is found through the above judgment that there is no normal IMU whose acceleration deviation and angular velocity deviation are both less than the corresponding deviation thresholds, it means that at least N-1 IMUs have hardware abnormalities, where N is the total number of IMUs. However, in order to ensure the safety of carrier movement, it can be considered that all IMUs have the possibility of hardware abnormalities and are all regarded as the first abnormal IMU. In this case, step S200 does not need to be executed, because the detection data of the IMU with hardware abnormality has problems, and the INS solution result is obtained based on the detection data processing, so the INS solution result will also be affected by the abnormality, so step S200 can be omitted.

[0081] On the contrary, when there are at least two normal IMUs, step S200 can be executed to determine whether there is a second abnormal IMU with software abnormality among all normal IMUs based on the INS solution results of each two normal IMUs. In this regard, in order to improve the acquisition efficiency of the second abnormal IMU, in some embodiments, the navigation device fault detection method provided by the embodiment of the present invention provides a way to implement step S200, that is, the INS solution result includes position information, attitude information and speed; accordingly, in the above step S200, the step of determining whether there is a second abnormal IMU with software abnormality among all normal IMUs based on the INS solution results of each two normal IMUs may include:

[0082] In step S210, it is determined whether the second abnormal IMU exists based on the position deviation between the position information and the set position deviation threshold, the attitude deviation between the attitude information and the set attitude deviation threshold, and the speed deviation between the speeds and the set speed deviation threshold in the INS solution results of each two normal IMUs.

[0083] Among them, at least one of the position deviation, attitude deviation or speed deviation between the second abnormal IMU and any IMU is not less than the corresponding deviation threshold.

[0084] In the process of determining whether there is a second abnormal IMU, step S210 may be performed to determine whether there is a second abnormal IMU among all normal IMUs. The principle of determining the second abnormal IMU is similar to the principle of determining the first abnormal IMU, and will not be described in detail here.

[0085] If there are only two normal IMUs determined in step S100, assuming that in fact, only one normal IMU has a software abnormality, then after processing in step S210, both normal IMUs will be considered to be the second abnormal IMU.

[0086] Therefore, through step S100 and step S200, a first abnormal IMU with hardware abnormality and a second abnormal IMU with software abnormality can be obtained.

[0087] Regardless of the execution order of step S100, during the execution of step S300, it is possible to determine whether there is an abnormal GNSS navigation module among all GNSS navigation modules based on the GNSS solution results of every two GNSS navigation modules belonging to different combined navigation devices. In this regard, in order to improve the efficiency of obtaining abnormal GNSS navigation modules, in some embodiments, the navigation device fault detection method provided by the embodiment of the present invention provides a way to implement step S300, that is, the GNSS solution result includes position information, attitude information and speed; accordingly, in the above step S300, the step of determining whether there is an abnormal GNSS navigation module among all GNSS navigation modules based on the GNSS solution results of every two GNSS navigation modules belonging to different combined navigation devices may include:

[0088] In step S310, it is determined whether there is an abnormal GNSS navigation module according to the position deviation between the position information and the set position deviation threshold, the attitude deviation between the attitude information and the set attitude deviation threshold, and the speed deviation between the speeds and the set speed deviation threshold in the GNSS solution results of every two GNSS navigation modules;

[0089] Wherein, at least one of the position deviation, attitude deviation or speed deviation between the abnormal GNSS navigation module and any GNSS navigation module is not less than the corresponding deviation threshold.

[0090] In the process of determining whether there is an abnormal GNSS navigation module, step S310 may be performed to determine whether there is an abnormal GNSS navigation module among all GNSS navigation modules. The principle of determining the abnormal GNSS navigation module is similar to the principle of determining the first abnormal IMU, which is not described in detail here.

[0091] The various thresholds mentioned above can be configured according to navigation accuracy requirements or experience, and the embodiment of the present invention does not limit this.

[0092] In the case that at least one of the first abnormal IMU, the second abnormal IMU or the abnormal GNSS navigation module has an abnormal device, step S500 may be executed to report all abnormal devices to the control module of the carrier. Thus, after the carrier learns all abnormal devices, the outputs of these abnormal devices may be ignored, effectively avoiding the impact on the safety and reliability of the carrier's movement due to continued use of fault information.

[0093] As can be seen from the above, for the sake of carrier movement safety, when it is impossible to accurately locate which device has an abnormality, all suspected abnormal devices will be regarded as abnormal devices and reported to the control module. It can be seen that the positioning accuracy of the abnormal device is low. Therefore, in order to solve this technical problem, in some embodiments, the navigation device fault detection method provided by the embodiment of the present invention also provides a multi-source fault detection solution, that is, each combined navigation device is configured with a Kalman filter and a state monitoring filter; accordingly, before reporting the abnormal device to the control module of the carrier, that is, before executing step S500, the navigation device fault detection method provided by the embodiment of the present invention may also include:

[0094] In step S410, for each integrated navigation device, a corresponding current estimated state matrix is ​​outputted through a Kalman filter in the integrated navigation device based on a current INS solution result and a current GNSS solution result respectively outputted by an IMU and a GNSS navigation module in the integrated navigation device at a current moment; the current estimated state matrix includes an estimated speed, an estimated position and an estimated attitude;

[0095] In step S420, for each integrated navigation device, a state monitoring filter in the integrated navigation device is used to output a corresponding current observation state matrix based on a current INS solution result output by an IMU in the integrated navigation device at the current moment; the current observation state matrix includes an observation speed, an observation position, and an observation attitude;

[0096] In step S430, for each integrated navigation device, a current state error matrix is ​​calculated according to the corresponding current estimated state matrix and the current observed state matrix; the current state error matrix includes the error between the corresponding estimated speed and the observed speed, the error between the corresponding estimated position and the observed position, and the error between the corresponding estimated attitude and the observed attitude;

[0097] In step S440, for each integrated navigation device, a fault detection value of the integrated navigation device is calculated according to the corresponding current state error matrix;

[0098] In step S450, a fault detection result of each integrated navigation device is obtained according to the fault detection value of each integrated navigation device and a preset fault threshold value; the fault detection result includes a normal result indicating that the integrated navigation device is normal, or an abnormal result indicating that the integrated navigation device is abnormal;

[0099] In step S460, a target abnormal component is determined from the determined abnormal components according to the fault detection result of the integrated navigation device.

[0100] Accordingly, in the above step S400, the step of reporting the abnormal device to the control module of the carrier is adjusted to: in the case where the target abnormal device exists, reporting the target abnormal device to the control module of the carrier.

[0101] Step S410 is essentially a state estimation scheme commonly used in combined navigation devices, and its purpose is to fuse data that does not pass through the sensor through a Kalman filter. In an embodiment of the present invention, it is used to fuse the data of the IMU and GNSS navigation modules in the same combined navigation device to filter out noise in the data and output more accurate position information, attitude information and speed.

[0102] Step S420 is essentially a scheme for state estimation based on the INS solution result of the IMU in the integrated navigation device. When the IMU and GNSS navigation modules in the integrated navigation device are both normal, the current observed state matrix output by the state monitoring filter in step S420 and the current estimated state matrix output by the Kalman filter should conform to the chi-square distribution. Otherwise, the two do not conform to the chi-square distribution. Therefore, the state monitoring filter and the Kalman filter can be combined to detect whether the integrated navigation device is faulty.

[0103] In the process of executing step S410, the current estimated state matrix at each current moment can be obtained by the following technical principles:

[0104]

[0105] In the above formula, represents the estimated state matrix at time k; I represents the identity matrix; K(k) represents the Kalman gain matrix at time k; H(k) represents the measurement noise matrix at time k, which can be obtained through relevant technologies; Φ(k / k-1) represents the state transfer matrix from time k-1 to time k, which can also be obtained through relevant technologies; represents the estimated state matrix at time k-1 obtained based on the estimation at time k-1, and Z(k) represents the matrix formed by the GNSS solution result input by the GNSS navigation module at time k. X(0) represents the estimated state matrix initialized at time 0, which is a Gaussian random vector and can be obtained through relevant technologies.

[0106] Among them, the Kalman gain matrix at time k can be obtained through the following technical principles:

[0107] K(k)=P G (k / k-1)H T (k)[H(k)P G (k / k-1)H T (k)+R(k)] -1

[0108] In the above formula, K(k) represents the Kalman gain matrix at time k, P G (k / k-1) represents the mean square error at time k derived from the mean square error at time k-1, H(k) represents the measurement noise matrix at time k, and H T (k) represents the transposed matrix of H(k), and R(k) represents the measurement error matrix at time k, which can be obtained through relevant techniques.

[0109] Among them, the mean square error P G (k / k-1) can be obtained through the following technical principles:

[0110] P G (k / k-1)

[0111] =Φ(k / k-1)P G (k-1)Φ T (k / k-1)

[0112] +Γ(k-1)Q(k-1)Γ T (k-1)

[0113] In the above formula, Φ(k / k-1) represents the state transition matrix from time k-1 to time k; P G (k-1) represents the mean square error estimated at time k-1; Φ T (k / k-1) represents the transposed matrix of Φ(k / k-1); Γ(k-1) represents the system noise driving matrix at time k-1, which can be understood as a matrix storing noise coefficients and can be obtained through related technologies; Q(k-1) represents the system noise matrix at time k-1; Γ T (k-1) represents the transposed matrix of Γ(k-1).

[0114] Based on this, the final estimated mean square error P at time k is G (k) can be obtained through the following technical principles:

[0115] P G (k)=[IK(k)H(k)]P G (k / k-1)

[0116] In the above formula, the meanings of the relevant letters can be found in the above description and will not be repeated here. G (0)=0, P(0) represents the initial value of the variance initialized at time 0, which can be obtained through relevant technologies.

[0117] Thus, after executing step S410, the current estimated state matrix output by the Kalman filter can be obtained. And the mean square error P at the current momentG (k).

[0118] In the process of executing step S420, the current observation state matrix at each current moment can be obtained by the following technical principles:

[0119]

[0120] In the above formula, represents the observed state matrix at time k, Φ(k / k-1) represents the state transfer matrix from time k-1 to time k, represents the observed state matrix at time k-1 estimated based on time k-1. X(0) represents the observation state matrix initialized at time 0, which is a Gaussian random vector and can be obtained through relevant techniques.

[0121] In addition, the mean square error at time k finally estimated by the state monitoring filter can be obtained through the following technical principles:

[0122] P F (k) = Φ(k / k-1)P F (k-1)Φ T (k / k-1)+Γ(k-1)Q(k-1)Γ T (k-1)

[0123] In the above formula, Φ(k / k-1) represents the state transition matrix from time k-1 to time k; P F (k-1) represents the mean square error estimated at time k-1; Φ T (k / k-1) represents the transposed matrix of Φ(k / k-1); Γ(k-1) represents the system noise driving matrix at time k-1, which can be understood as a matrix storing noise coefficients and can be obtained through related technologies; Q(k-1) represents the system noise matrix at time k-1; Γ T (k-1) represents the transposed matrix of Γ(k-1). F (0)=P(0), P(0) represents the initial value of the variance initialized at time 0, which can be obtained through relevant technologies.

[0124] It can be seen that for the state monitoring filter, there is no need to calculate the Kalman gain or the predicted P F (k / k-1).

[0125] Thus, after executing step S420, the current observation state matrix output by the state monitoring filter can be obtained: And the mean square error P at the current moment F (k).

[0126] In addition, as the continuous working time of the state monitoring filter increases, its own error will become larger and larger, which will lead to an increasing mean square error, thereby affecting the accuracy of fault detection. Therefore, in order to solve this technical problem, in some embodiments, the navigation device fault detection method provided in the embodiment of the present invention proposes two solutions:

[0127] The first one: There are two condition monitoring filters configured.

[0128] Accordingly, in the above step S420, the step of outputting the corresponding current observation state matrix based on the current INS solution result output by the IMU in the integrated navigation device at the current moment through the state monitoring filter in the integrated navigation device may include:

[0129] In step S4211, when the monitoring duration of the currently selected current state monitoring filter does not reach half of the set monitoring period, the observation state matrix output by the current state monitoring filter based on the current INS solution result is discarded;

[0130] In step S4212, when the monitoring duration of the current state monitoring filter reaches half of the set monitoring period, the observation state matrix output by the current state monitoring filter based on the current INS solution result is used as the current observation state matrix, and another state monitoring filter is initialized; wherein the monitoring duration of the initialized another state monitoring filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at the time of its initialization;

[0131] In step S4213, when the monitoring duration of the current state monitoring filter reaches the set monitoring period, the current state monitoring rate filter is initialized, and the other state monitoring filter is used as the current state monitoring filter; wherein, the monitoring duration of the initialized current state monitoring rate filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at its initialization time.

[0132] For the above steps S4211 to S4213, it can be understood that two state monitoring filters are used to work alternately and initialize alternately. For example, for the state monitoring filter S1 and the state monitoring filter S2, it is assumed that their monitoring cycles are both 10s. It is assumed that in a certain fault monitoring process, the initialized state monitoring filter S1 is selected. Since the state quantity used by the state monitoring filter S1 during initialization is the estimated state quantity output by the Kalman filter at the initialization time, the output result of the first half of the state monitoring filter cycle, that is, the first 5s, is greatly affected by the initialized state quantity, which may affect the accuracy of the subsequent fault detection results. Therefore, the output result of the first 5s is not used for fault detection. In the last 5s, the output result of the state monitoring filter tends to be stable, so the output result of the last 5s can be used for fault detection. At the same time, in order to ensure that after the state monitoring filter S1 ends a monitoring cycle, the output result of the switched state monitoring filter S2 can be immediately applied to fault detection, the state monitoring filter S2 can be initialized when the state monitoring filter S1 works to the 6th second. In this way, after the state monitoring filter S1 has finished working once, the corresponding working time of the state monitoring filter S2 is 5 seconds, so the output result of the state monitoring filter S2 can be immediately used for fault detection in the next second after the switch.

[0133] It can be seen that the use of two state monitoring filters to work alternately can ensure seamless fault detection, which is beneficial to improving the comprehensiveness and reliability of fault detection.

[0134] The second type: There is only one condition monitoring filter.

[0135] Accordingly, in the above step S420, the step of outputting the corresponding current observation state matrix based on the current INS solution result output by the IMU in the integrated navigation device at the current moment through the state monitoring filter in the integrated navigation device may include:

[0136] In step S4221, when the monitoring duration of the state monitoring filter does not reach half of the set monitoring period, the observation state matrix output by the state monitoring filter based on the current INS solution result is discarded;

[0137] In step S4222, when the monitoring time of the state monitoring filter reaches half of the set monitoring period, the observation state matrix output by the state monitoring filter based on the current INS solution result is used as the current observation state matrix;

[0138] In step S4223, when the monitoring duration of the state monitoring filter reaches the set monitoring period, the state monitoring filter is initialized; wherein, the monitoring duration of the initialized state monitoring filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at the time of its initialization.

[0139] The difference between the second solution and the first solution is that the second solution uses one condition monitoring filter to replace two condition monitoring filters for operation. The operating principle is similar to that of the first solution, but because there is only one condition monitoring filter, half of the monitoring cycles in each monitoring cycle cannot be used for fault diagnosis, that is, there is a monitoring gap. The second solution can save device costs.

[0140] The first and second solutions mentioned above can be selected according to actual needs.

[0141] The current estimated state matrix is ​​obtained by any of the above embodiments The mean square error P at the current moment G (k), current observation state matrix And the mean square error P at the current moment F (k) After that, step S430 may be performed to calculate the current state error matrix for each integrated navigation device according to the corresponding current estimated state matrix and current observed state matrix. Taking an integrated navigation device as an example, the calculation principle of the current state error matrix is ​​as follows:

[0142] β(k)=e G (k)-e F (k)

[0143] Among them, β(k) represents the state error matrix at time k, e G (k) represents the estimation error of the estimated state matrix at time k, e F (k) represents the estimation error of the observation state matrix at time k.

[0144] In the above, e G (k) and e F (k) can be calculated by the following technical principle:

[0145]

[0146] Among them, X(k) represents the matrix composed of the INS solution results at time k, and The meaning of is as described above and will not be elaborated here.

[0147] After the current state error matrix is ​​obtained in step S430, step S440 may be performed to calculate the fault detection value of each integrated navigation device according to the corresponding current state error matrix. The calculation principle is as follows:

[0148] λ(k)=β T (k)T -1 (k)β(k)

[0149] In the above formula, λ(k) represents the fault detection value at time k, β(k) represents the state error matrix at time k, and β T (k) represents the transposed matrix of β(k), T -1 (k) represents the inverse of the variance T(k) of β(k).

[0150] The calculation principle of T(k) is as follows:

[0151] T(k)=S{β(k)β T (k)}

[0152] =S{e G (k)e G T (k)-e G (k)e F T (k)-e F (k)e G T (k)+e F (k)e F T (k)}

[0153] In the above, S{} is a variance calculation function, and the meanings of other letters are recorded above and will not be repeated here.

[0154] Therefore, the fault detection value at the current moment can be obtained by executing step S440.

[0155] Next, step S450 may be performed to obtain the fault detection result of each integrated navigation device according to the fault detection value of each integrated navigation device and the preset fault threshold value. That is, assuming that the fault threshold value is T D , then the fault detection value λ(k) at the current moment>T D In the case of λ(k)≤T D In the case of , it means that the corresponding combined navigation device is normal.

[0156] Among them, T D It can be obtained through the following principles:

[0157] Since β(k) is a Gaussian random variable e G (k) and e F (k), so β(k) is also a Gaussian random variable with mean 0.

[0158] After a lot of tests, it is found that β(k) has different performances when the integrated navigation equipment is abnormal or normal, as follows:

[0159] When the integrated navigation device is normal, the mean value of β(k) is 0, and its variance satisfies T(k)=S{β(k)β T (k)}.

[0160] In the case of an abnormal integrated navigation device, the mean of β(k) is not 0, and its variance satisfies T(k)=S{[β(k)-μ][β T (k)]-μ}, where μ is the mean of β(k) in this case.

[0161] Therefore, based on the above two performance conditions, the fault threshold value T can be calculated. D The value of , the calculation principle of which can be found in the relevant technology.

[0162] Therefore, step S450 can be used to determine whether there are any abnormal combined navigation devices and which combined navigation devices are abnormal.

[0163] Next, step S460 may be executed to determine the target abnormal device from the determined abnormal devices according to the fault detection result of the combined navigation device. It can be understood that the target abnormal device is located together by combining the multi-source fault detection results and the same-source fault detection results to achieve accurate positioning of the target abnormal device. In this regard, in order to achieve accurate positioning of the target abnormal device, in some embodiments, the navigation device fault detection method provided in the embodiment of the present invention also proposes an implementation scheme of step S460, that is, in the above step S460, the step of determining the target abnormal device from the determined abnormal devices according to the fault detection result of the combined navigation device may include:

[0164] In step S461, for each abnormal device, if the fault detection result of the combined navigation device to which the abnormal device belongs is a normal result, the fault detection result of the abnormal device is updated to normal; if the fault detection result of the combined navigation device to which the abnormal device belongs is an abnormal result, the abnormal device is determined as a target abnormal device.

[0165] For example, it is assumed that through steps S100 to S300, the abnormal devices in the IMU that have been determined are A1, A2, and A3; the abnormal devices in the GNSS navigation module are B1 and B4; the abnormal combined navigation devices are C1 and C3; among which, C1 includes A1 and B1, and C3 includes A3 and B3. Based on this, it can be seen that among the combined navigation devices, there are abnormal devices in A1, B1, A3, and B3, and the abnormal devices that have been determined are A1, A2, A3, B1, and B4. Therefore, it can be seen that A1 and B1 are both abnormal devices that have been determined, and the combined navigation device C1 to which they belong is also determined to be abnormal, so A1 and B1 are the target abnormal devices. The combined navigation device C2 to which A2 belongs is determined to be normal, so A2 can be excluded and its detection result can be updated to normal. A3 is also an abnormal device that has been determined, but B3 is a normal device that has been determined, and the integrated navigation device C3 to which it belongs is also determined to be abnormal, so it can be considered that the abnormality of C3 is caused by A3, so A3 is the target abnormal device, and B3 is normal. For B4, since the integrated navigation device C4 to which it belongs is determined to be normal, B4 can be excluded and its detection result is updated to normal.

[0166] Therefore, by combining the fault detection results of the same source and multiple sources to further screen the identified abnormal devices, the devices that are misjudged as abnormal can be eliminated, and then the truly abnormal devices - the target abnormal devices - can be screened out, effectively improving the accuracy of locating the target abnormal devices, as well as the effectiveness and reliability of fault reporting.

[0167] In addition, the fault detection results of the same source and multiple sources can be combined to determine whether the normal components determined by the same source detection method are indeed normal. In view of this, in some embodiments, the navigation device fault detection method provided by the embodiment of the present invention can also include:

[0168] In step S470, for each normal component that has been determined, if the fault detection result of the combined navigation device to which the normal component belongs is a normal result, or if the fault detection result of the combined navigation device to which the normal component belongs is an abnormal result and another component in the combined navigation device to which the normal component belongs is an abnormal component that has been determined, then the normal component is determined to be normal; if the fault detection result of the combined navigation device to which the normal component belongs is an abnormal result and another component in the combined navigation device to which the normal component belongs is not an abnormal component that has been determined, then the normal component and the other component in the combined navigation device to which the normal component belongs are determined as target abnormal components.

[0169] For example, assuming that through steps S100 to S300, the normal components in the IMU that have been determined are A1 and A3; the normal components in the GNSS navigation module are B2 and B3; and the abnormal combined navigation devices are C1 and C3; wherein C1 includes A1 and B1, and C3 includes A3 and B3. Based on this, it can be seen that the fault detection result of the combined navigation device C1 to which the normal component A1 belongs is an abnormal result, and another component B1 in the combined navigation device C1 is the determined abnormal component. Therefore, it can be considered that the fault of the combined navigation device C1 is caused by the abnormal component B1, so it can be determined that A1 is indeed a normal component.

[0170] For A3 and B3, the fault detection results of the combined navigation device C3 to which they belong are abnormal results, but A3 and B3 are not determined abnormal components. Therefore, it can be considered that the fault of C3 is caused by at least one of A3 or B3. Therefore, for safety reasons, A3 and B3 are both determined as abnormal components.

[0171] For B2, since the fault detection result of the integrated navigation device C2 to which it belongs is a normal result, it can be determined that B2 is indeed a normal device.

[0172] Therefore, by combining the results of homologous detection and multi-source detection to screen normal devices, it is possible to locate faulty devices more comprehensively and accurately, thereby improving the movement reliability and movement safety of the carrier.

[0173] After obtaining the target abnormal device through any of the above embodiments, step S500 may be performed to report the target abnormal device to the control module.

[0174] In addition, in some embodiments, relevant information of the target abnormal device may be sent to the bound user terminal to remind relevant personnel to perform troubleshooting or maintenance of the abnormal device.

[0175] It is worth noting that the technical features or technical solutions in any of the above embodiments of the present invention can be combined with each other as long as there is no combination contradiction.

[0176] In addition, an embodiment of the present invention further provides a carrier, including:

[0177] Body;

[0178] A plurality of combined navigation devices are respectively installed at different parts of the aircraft body;

[0179] A control module, used for controlling the operation of the body according to the outputs of the plurality of combined navigation devices;

[0180] A fault detection module is used to execute the navigation device fault detection method provided in any of the above embodiments of the present invention, so as to determine whether there are abnormal components in the multiple combined navigation devices based on the outputs of the multiple combined navigation devices, and report to the control module if there are abnormal components.

[0181] The fault detection principle can be found in the relevant description of the method embodiment, which will not be elaborated here.

[0182] In order to execute the corresponding steps in the above method embodiment and various possible methods, a method for implementing a navigation device fault detection device is given below. Optionally, the navigation device fault detection device can adopt the above method. Figure 1 For further information, please refer to Figure 3 , Figure 3 This is a functional module diagram of a navigation device fault detection device provided by an embodiment of the present invention. It should be noted that the basic principle and technical effect of the navigation device fault detection device provided by this embodiment are the same as those of the above method embodiment. For the sake of brief description, for the parts not mentioned in this embodiment, reference can be made to the corresponding contents in the above method embodiment. The navigation device fault detection device 300 includes:

[0183] The hard fault determination module 310 is configured to: determine whether there is a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware among all the IMUs according to the detection data of every two IMUs belonging to different integrated navigation devices;

[0184] The soft fault determination module 320 is configured to: when there are at least two normal IMUs, determine whether there is a second abnormal IMU with software abnormality among all the normal IMUs according to the INS solution results of every two normal IMUs;

[0185] The GNSS fault determination module 330 is configured to: determine whether there is an abnormal GNSS navigation module among all the GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different combined navigation devices;

[0186] The reporting module 340 is configured to: in the event that at least one of the first abnormal IMU, the second abnormal IMU, or the abnormal GNSS navigation module has an abnormal component, report the abnormal component to the control module of the carrier.

[0187] In some embodiments, each combined navigation device is configured with a Kalman filter and a state monitoring filter. Accordingly, before the reporting module 340 reports the abnormal device to the control module of the carrier, the navigation device fault detection device 300 provided in the embodiment of the present invention may also include:

[0188] The state estimation module is configured to: for each integrated navigation device, output a corresponding current estimated state matrix through a Kalman filter in the integrated navigation device based on a current INS solution result and a current GNSS solution result respectively output by an IMU and a GNSS navigation module in the integrated navigation device at a current moment; the current estimated state matrix includes an estimated speed, an estimated position, and an estimated attitude;

[0189] The state monitoring module is configured to: for each integrated navigation device, output a corresponding current observation state matrix based on a current INS solution result output by an IMU in the integrated navigation device at a current moment through a state monitoring filter in the integrated navigation device; the current observation state matrix includes an observation speed, an observation position and an observation attitude;

[0190] The multi-source error calculation module is configured to: for each integrated navigation device, calculate a current state error matrix according to the corresponding current estimated state matrix and the current observed state matrix; the current state error matrix includes the error between the corresponding estimated speed and the observed speed, the error between the corresponding estimated position and the observed position, and the error between the corresponding estimated attitude and the observed attitude;

[0191] The fault value calculation module is configured to: for each integrated navigation device, calculate the fault detection value of the integrated navigation device according to the corresponding current state error matrix;

[0192] The fault result determination module is configured to: obtain the fault detection result of each integrated navigation device according to the fault detection value of each integrated navigation device and the preset fault threshold value; the fault detection result includes a normal result indicating that the integrated navigation device is normal, or an abnormal result indicating that the integrated navigation device is abnormal;

[0193] A target abnormal device determination module is configured to: determine a target abnormal device from the determined abnormal devices according to the fault detection result of the integrated navigation device;

[0194] Accordingly, the reporting module 340 is adjusted and configured to: in the case where there is a target abnormal device, report the target abnormal device to the control module of the carrier.

[0195] In some embodiments, the state monitoring filter is configured with two. Accordingly, the process of the state monitoring module outputting the corresponding current observation state matrix through the state monitoring filter in the integrated navigation device based on the current INS solution result output by the IMU in the integrated navigation device at the current moment is configured as follows:

[0196] When the monitoring time of the currently selected current state monitoring filter does not reach half of the set monitoring period, the observation state matrix output by the current state monitoring filter based on the current INS solution result is discarded;

[0197] When the monitoring duration of the current state monitoring filter reaches half of the set monitoring period, the observation state matrix output by the current state monitoring filter based on the current INS solution result is used as the current observation state matrix, and another state monitoring filter is initialized; wherein the monitoring duration of the initialized another state monitoring filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at the time of its initialization;

[0198] When the monitoring duration of the current state monitoring filter reaches the set monitoring period, the current state monitoring rate filter is initialized, and the other state monitoring filter is used as the current state monitoring filter; wherein the monitoring duration of the initialized current state monitoring rate filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at its initialization time.

[0199] In some other embodiments, the state monitoring filter configuration is configured with only one. Accordingly, the process of the state monitoring module outputting the corresponding current observation state matrix through the state monitoring filter in the integrated navigation device based on the current INS solution result output by the IMU in the integrated navigation device at the current moment is configured as follows:

[0200] When the monitoring time of the state monitoring filter does not reach half of the set monitoring period, discarding the observation state matrix output by the state monitoring filter based on the current INS solution result;

[0201] When the monitoring time of the state monitoring filter reaches half of the set monitoring period, the observation state matrix output by the state monitoring filter based on the current INS solution result is used as the current observation state matrix;

[0202] When the monitoring duration of the state monitoring filter reaches the set monitoring period, the state monitoring filter is initialized; wherein, the monitoring duration of the initialized state monitoring filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at its initialization time.

[0203] In some embodiments, the process of determining the target abnormal device from the determined abnormal devices by the target abnormal device determination module according to the fault detection result of the combined navigation device is configured as follows:

[0204] For each abnormal component, if the fault detection result of the combined navigation device to which the abnormal component belongs is a normal result, the fault detection result of the abnormal component is updated to normal; if the fault detection result of the combined navigation device to which the abnormal component belongs is an abnormal result, the abnormal component is determined as a target abnormal component.

[0205] In some embodiments, the target abnormal device determination module is further configured to:

[0206] For each normal component that has been determined, if the fault detection result of the combined navigation device to which the normal component belongs is a normal result, or if the fault detection result of the combined navigation device to which the normal component belongs is an abnormal result and another component in the combined navigation device to which the normal component belongs is an abnormal component that has been determined, then the normal component is determined to be normal; if the fault detection result of the combined navigation device to which the normal component belongs is an abnormal result and another component in the combined navigation device to which the normal component belongs is not an abnormal component that has been determined, then the normal component and the other component in the combined navigation device to which the normal component belongs are determined as target abnormal components.

[0207] In some embodiments, the detection data includes acceleration and angular velocity. Accordingly, the process of the hard fault determination module 310 determining a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware according to the detection data of each two IMUs belonging to different combined navigation devices is configured as follows:

[0208] According to the acceleration deviation between the accelerations detected by every two IMUs and the set acceleration deviation threshold, and the angular velocity deviation between the angular velocities detected by every two IMUs and the set angular velocity deviation threshold, the normal IMU and the first abnormal IMU are obtained;

[0209] Among them, the acceleration deviation and angular velocity deviation between the normal IMU and the normal IMU are both smaller than their corresponding deviation thresholds, and at least one of the acceleration deviation or angular velocity deviation between the first abnormal IMU and any IMU is not smaller than the corresponding deviation threshold.

[0210] In some embodiments, the INS solution result includes position information, attitude information and speed. Accordingly, the process of the soft fault determination module 320 determining whether there is a second abnormal IMU with software abnormality among all normal IMUs according to the INS solution results of every two normal IMUs is configured as follows:

[0211] Determine whether there is the second abnormal IMU according to the position deviation between the position information and the set position deviation threshold, the attitude deviation between the attitude information and the set attitude deviation threshold, and the speed deviation between the speeds and the set speed deviation threshold in the INS solution results of each two normal IMUs;

[0212] Among them, at least one of the position deviation, attitude deviation or speed deviation between the second abnormal IMU and any IMU is not less than the corresponding deviation threshold.

[0213] In some embodiments, the GNSS solution result includes position information, attitude information and speed. Accordingly, the process of the GNSS fault determination module 330 determining whether there is an abnormal GNSS navigation module among all GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different combined navigation devices is configured as follows:

[0214] Determine whether there is an abnormal GNSS navigation module according to the position deviation between the position information and the set position deviation threshold, the attitude deviation between the attitude information and the set attitude deviation threshold, and the speed deviation between the speeds and the set speed deviation threshold in the GNSS solution results of every two GNSS navigation modules;

[0215] Wherein, at least one of the position deviation, attitude deviation or speed deviation between the abnormal GNSS navigation module and any GNSS navigation module is not less than the corresponding deviation threshold.

[0216] Optionally, the above modules can be stored in the form of software or firmware. Figure 1 The memory shown in the figure or solidified in the operating system (OS) of the electronic device, and can be Figure 1 Meanwhile, the data and program codes required for executing the above modules can be stored in the memory.

[0217] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0218] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0219] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0220] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A navigation device fault detection method, characterized in that: Used to perform fault detection on multiple integrated navigation devices installed on a carrier, each integrated navigation device includes an IMU and a GNSS navigation module; the method includes: Determine, according to detection data of every two IMUs belonging to different integrated navigation devices, whether there is a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware among all the IMUs; In the case where there are at least two normal IMUs, determining whether there is a second abnormal IMU with software abnormality among all the normal IMUs according to the INS solution results of every two normal IMUs; Determine whether there is an abnormal GNSS navigation module among all the GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different integrated navigation devices; In the case that at least one abnormal device among the first abnormal IMU, the second abnormal IMU, or the abnormal GNSS navigation module exists, the abnormal device is reported to the control module of the carrier.

2. The method according to claim 1, characterized in that Each integrated navigation device is configured with a Kalman filter and a state monitoring filter; before reporting the abnormal device to the control module of the carrier, the method further includes: For each integrated navigation device, outputting a corresponding current estimated state matrix through a Kalman filter in the integrated navigation device based on a current INS solution result and a current GNSS solution result respectively outputted by an IMU and a GNSS navigation module in the integrated navigation device at a current moment; the current estimated state matrix includes an estimated speed, an estimated position, and an estimated attitude; For each integrated navigation device, outputting a corresponding current observation state matrix based on a current INS solution result output by an IMU in the integrated navigation device at the current moment through a state monitoring filter in the integrated navigation device; the current observation state matrix includes an observation speed, an observation position and an observation attitude; For each integrated navigation device, a current state error matrix is ​​calculated based on the corresponding current estimated state matrix and the current observed state matrix; the current state error matrix includes the error between the corresponding estimated speed and the observed speed, the error between the corresponding estimated position and the observed position, and the error between the corresponding estimated attitude and the observed attitude; For each integrated navigation device, a fault detection value of the integrated navigation device is calculated according to the corresponding current state error matrix; Obtaining a fault detection result of each integrated navigation device according to the fault detection value of each integrated navigation device and a preset fault threshold value; the fault detection result includes a normal result indicating that the integrated navigation device is normal, or an abnormal result indicating that the integrated navigation device is abnormal; According to the fault detection result of the integrated navigation device, determining a target abnormal device from the determined abnormal devices; Correspondingly, the step of reporting the abnormal device to the control module of the carrier is adjusted to: in the case where the target abnormal device exists, reporting the target abnormal device to the control module of the carrier.

3. The method according to claim 2, characterized in that The state monitoring filter is configured with two; the step of outputting the corresponding current observation state matrix based on the current INS solution result output by the IMU in the integrated navigation device at the current moment through the state monitoring filter in the integrated navigation device comprises: When the monitoring time of the currently selected current state monitoring filter does not reach half of the set monitoring period, the observation state matrix output by the current state monitoring filter based on the current INS solution result is discarded; When the monitoring duration of the current state monitoring filter reaches half of the set monitoring period, the observation state matrix output by the current state monitoring filter based on the current INS solution result is used as the current observation state matrix, and another state monitoring filter is initialized; wherein the monitoring duration of the initialized another state monitoring filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at the time of its initialization; When the monitoring duration of the current state monitoring filter reaches the set monitoring period, the current state monitoring rate filter is initialized, and the other state monitoring filter is used as the current state monitoring filter; wherein the monitoring duration of the initialized current state monitoring rate filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at its initialization time.

4. The method according to claim 2, characterized in that: The state monitoring filter is only configured with one; the step of outputting the corresponding current observation state matrix based on the current INS solution result output by the IMU in the integrated navigation device at the current moment through the state monitoring filter in the integrated navigation device includes: When the monitoring time of the state monitoring filter does not reach half of the set monitoring period, discarding the observation state matrix output by the state monitoring filter based on the current INS solution result; When the monitoring time of the state monitoring filter reaches half of the set monitoring period, the observation state matrix output by the state monitoring filter based on the current INS solution result is used as the current observation state matrix; When the monitoring duration of the state monitoring filter reaches the set monitoring period, the state monitoring filter is initialized; wherein, the monitoring duration of the initialized state monitoring filter is updated to 0, and its initial state matrix is ​​updated to the current state estimation matrix output by the Kalman filter at its initialization time.

5. The method according to claim 2, characterized in that: The step of determining a target abnormal device from the determined abnormal devices according to the fault detection result of the integrated navigation device comprises: For each abnormal component, if the fault detection result of the combined navigation device to which the abnormal component belongs is a normal result, the fault detection result of the abnormal component is updated to normal; if the fault detection result of the combined navigation device to which the abnormal component belongs is an abnormal result, the abnormal component is determined as a target abnormal component.

6. The method according to claim 2, characterized in that The method further comprises: For each normal component that has been determined, if the fault detection result of the combined navigation device to which the normal component belongs is a normal result, or if the fault detection result of the combined navigation device to which the normal component belongs is an abnormal result and another component in the combined navigation device to which the normal component belongs is an abnormal component that has been determined, then the normal component is determined to be normal; if the fault detection result of the combined navigation device to which the normal component belongs is an abnormal result and another component in the combined navigation device to which the normal component belongs is not an abnormal component that has been determined, then the normal component and the other component in the combined navigation device to which the normal component belongs are determined as target abnormal components.

7. The method according to claim 1, characterized in that The detection data includes acceleration and angular velocity; the step of determining a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware according to the detection data of each two IMUs belonging to different combined navigation devices comprises: According to the acceleration deviation between the accelerations detected by every two IMUs and the set acceleration deviation threshold, and the angular velocity deviation between the angular velocities detected by every two IMUs and the set angular velocity deviation threshold, the normal IMU and the first abnormal IMU are obtained; Among them, the acceleration deviation and angular velocity deviation between the normal IMU and the normal IMU are both smaller than their corresponding deviation thresholds, and at least one of the acceleration deviation or angular velocity deviation between the first abnormal IMU and any IMU is not smaller than the corresponding deviation threshold.

8. The method according to claim 1, characterized in that The INS solution results include position information, attitude information and speed; The step of determining whether there is a second abnormal IMU with software abnormality among all normal IMUs according to the INS solution results of every two normal IMUs comprises: Determine whether there is the second abnormal IMU according to the position deviation between the position information and the set position deviation threshold, the attitude deviation between the attitude information and the set attitude deviation threshold, and the speed deviation between the speeds and the set speed deviation threshold in the INS solution results of each two normal IMUs; Among them, at least one of the position deviation, attitude deviation or speed deviation between the second abnormal IMU and any IMU is not less than the corresponding deviation threshold.

9. The method according to claim 1, characterized in that: The GNSS solution result includes position information, attitude information and speed; the step of determining whether there is an abnormal GNSS navigation module in all GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different combined navigation devices includes: Determine whether there is an abnormal GNSS navigation module according to the position deviation between the position information and the set position deviation threshold, the attitude deviation between the attitude information and the set attitude deviation threshold, and the speed deviation between the speeds and the set speed deviation threshold in the GNSS solution results of every two GNSS navigation modules; Wherein, at least one of the position deviation, attitude deviation or speed deviation between the abnormal GNSS navigation module and any GNSS navigation module is not less than the corresponding deviation threshold.

10. A navigation equipment fault detection device, characterized in that: Used to perform fault detection on multiple integrated navigation devices installed on a carrier, each integrated navigation device includes an IMU and a GNSS navigation module; the device includes: The hard fault determination module is configured to: determine whether there is a normal IMU with normal hardware and a first abnormal IMU with abnormal hardware among all the IMUs according to the detection data of every two IMUs belonging to different combined navigation devices; The soft fault determination module is configured to: when there are at least two normal IMUs, determine whether there is a second abnormal IMU with software abnormality among all the normal IMUs according to the INS solution results of every two normal IMUs; The GNSS fault determination module is configured to: determine whether there is an abnormal GNSS navigation module among all the GNSS navigation modules according to the GNSS solution results of every two GNSS navigation modules belonging to different combined navigation devices; The reporting module is configured to: in the event that at least one abnormal device among the first abnormal IMU, the second abnormal IMU, or the abnormal GNSS navigation module exists, report the abnormal device to the control module of the carrier.

11. An electronic device, characterized in that: The invention comprises a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor can execute the machine executable instructions to implement the method according to any one of claims 1 to 9.

12. A carrier, characterized in that include: Body; A plurality of combined navigation devices are respectively installed at different parts of the aircraft body; A control module, used for controlling the operation of the body according to the outputs of the plurality of combined navigation devices; A fault detection module, used to execute the method described in any one of claims 1 to 9, to determine whether there are abnormal components in the multiple combined navigation devices based on the outputs of the multiple combined navigation devices, and to report to the control module if there are abnormal components.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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