KR102414141B1 - Method and apparatus for derivative of noise source in aerial vehicle - Google Patents

Abstract

An apparatus for deriving a noise source from a vehicle according to an embodiment includes a data collection unit that collects sensor data from the vehicle, and a data selection unit that selects sensor data of at least one field from among a plurality of fields included in the collected sensor data; , a noise source deriving unit deriving at least a portion of the selected sensor data as a noise source.

Description

Apparatus and method for deriving a noise source from a vehicle

The present invention relates to a device for deriving a noise source from an aircraft and a method for such a device to derive a noise source from an aircraft.

When operating an unmanned aerial vehicle, in order to send and receive safe communication between the control center and the vehicle, a new number that has not been used in the previous communication, is unpredictable and cannot be reused, is required per session, and this requires a noise source that is the source of the unpredictable number.

However, since the control center is an IT environment with PCs or servers, numerous data can be used as the source source to generate irregular numbers, but the source source for outputting unpredictable numbers in the firmware-based unmanned aerial vehicle is the IT environment. markedly lacking compared to

If the unmanned aerial vehicle is operated within line-of-sight, the need for noise sources that become an unpredictable number of sources when communicating with the control center may not be great. Therefore, in order to enhance the stability of communication between the control center and the unmanned aerial vehicle, the unmanned aerial vehicle must derive an unpredictable number of sources of noise.

Republic of Korea Patent Publication No. 10-1694115, registration date January 03, 2017.

One embodiment of the present invention provides an apparatus and method for deriving noise sources that are sources of unpredictable numbers in a vehicle.

The problems to be solved of the present invention are not limited to those mentioned above, and other problems to be solved that are not mentioned will be clearly understood by those of ordinary skill in the art to which the present invention belongs from the following description.

The apparatus for deriving a noise source from an aircraft according to the first aspect includes a data collection unit for collecting sensor data from the vehicle, and a data selection unit for selecting sensor data of at least one field among a plurality of fields included in the collected sensor data; , a noise source deriving unit deriving at least a portion of the selected sensor data as a noise source.

The noise source derivation method performed by the device for deriving a noise source from a vehicle according to a second aspect includes the steps of collecting sensor data from the vehicle, and selecting sensor data of at least one field among a plurality of fields included in the collected sensor data and deriving at least a portion of the selected sensor data as a noise source.

The computer-readable recording medium storing the computer program according to the third aspect includes the steps of, when the computer program is executed by a processor, collecting sensor data from the vehicle, and a plurality of fields included in the collected sensor data and instructions for causing the processor to perform a method comprising: selecting at least one field of sensor data; and deriving at least a portion of the selected sensor data as a noise source.

The computer program stored in the computer-readable recording medium according to the fourth aspect includes the steps of, when the computer program is executed by a processor, collecting sensor data from the vehicle; a plurality of fields included in the collected sensor data and instructions for causing the processor to perform a method comprising: selecting at least one field of sensor data; and deriving at least a portion of the selected sensor data as a noise source.

According to an embodiment of the present invention, it is possible to derive a noise source that is an unpredictable number of sources from various sensor data of an aircraft. Accordingly, even in an environment in which the control center cannot provide a noise source to the vehicle, it is possible to derive a noise source that the vehicle can use for safe communication, so that safe communication between the vehicle and the control center can be performed.

1 is a block diagram of an apparatus for deriving a noise source in an aircraft according to an embodiment of the present invention.
2 and 3 are flowcharts for explaining a method of deriving a noise source from an aircraft according to an embodiment of the present invention.
Figure 4 is an exemplary view of sensor data by the MPU6050 module that can be mounted on the vehicle.
5 is an example of a noise source that can be derived from sensor data by the noise source derivation apparatus according to an embodiment of the present invention.

Advantages and features of the present invention and methods of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but can be implemented in various forms, and only these embodiments allow the disclosure of the present invention to be complete, and those of ordinary skill in the art to which the present invention pertains. It is provided to fully inform the person of the scope of the invention, and the scope of the invention is only defined by the claims.

In describing the embodiments of the present invention, detailed descriptions of well-known functions or configurations will be omitted except when it is actually necessary to describe the embodiments of the present invention. In addition, the terms to be described later are terms defined in consideration of functions in an embodiment of the present invention, which may vary according to intentions or customs of users and operators. Therefore, the definition should be made based on the content throughout this specification.

In this specification, the singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as 'comprise' or 'comprise' are intended to designate that a feature, number, step, operation, component, part, or a combination thereof described in the specification exists, but one or more other It should be understood that this does not preclude the possibility of addition or presence of features or numbers, steps, operations, components, parts, or combinations thereof.

Also, in an embodiment of the present invention, when it is said that a part is connected to another part, this includes not only direct connection but also indirect connection through another medium. In addition, the meaning that a certain part includes a certain component means that other components may be further included, rather than excluding other components, unless specifically stated to the contrary.

1 is a block diagram of an apparatus for deriving a noise source in an aircraft according to an embodiment of the present invention.

Referring to FIG. 1 , an apparatus 100 for deriving a noise source according to an embodiment includes a data collection unit 110 , a data selection unit 120 , and a noise source derivation unit 130 , and further includes a storage unit 140 . can do.

The data collection unit 110 collects sensor data from the vehicle and provides it to the data selection unit 120 . For example, the data collection unit 110 may collect at least one of GPS data, accelerometer data, gyro sensor data, magnetometer data, barometer data, range finder data, inertial data, and motor RPM data. The data collection unit 110 may include, for example, an interface capable of receiving sensor data from various sensors.

The data selection unit 120 selects sensor data of at least one field from among a plurality of fields included in the sensor data collected by the data collection unit 110 and provides it to the noise source derivation unit 130 . For example, when the data collection unit 110 provides GPS data in the GPGGA format, the data selection unit 120 sets the UTC Time field, Latitude field, Longitude field, Satellites Used field, HDOP field, Altitude field, and Geoid Separation field. The sensor data of at least one of the field and the checksum field may be selected and provided to the noise source deriving unit 130 . When the data collection unit 110 provides GPS data in the GPRMC format, the data selection unit 120 performs the UTC Time field, Latitude field, Longitude field, Speed over ground field, Course over ground field, Magnetic variation field, and Checksum field. Among them, sensor data of at least one field may be selected and provided to the noise source derivation unit 130 . When the data collection unit 110 provides GPS data in the GPGSV format, the data selection unit 120 selects the sensor data of at least one of the SNR 1 field, the SNR 2 field, the SNR 3 field, the SNR 4 field, and the Checksum field. It may be selected and provided to the noise source derivation unit 130 . For example, the data selection unit 120 may include a computing unit such as a microprocessor.

The noise source deriving unit 130 derives at least a portion of the sensor data selected by the data selecting unit 120 as a noise source. For example, when the sensor data selected by the data selection unit 120 has a plurality of digits, the noise source derivation unit 130 selects at least one digit position based on the width that varies with respect to the plurality of digits, A plurality of sensor data according to the passage of time of the selected seat position may be derived as a noise source. In this case, the noise source derivation unit 130 may give a rank of change rate for each seat position based on a width that changes with respect to a plurality of digits, and may derive a noise source based on the rank of change rate. For example, the noise source derivation unit 130 may calculate a change amount score for each seat position as an entropy value of the entropy evaluation tool, and may give a change rate ranking according to the change amount score. In addition, the noise source derivation unit 130 may prevent unnecessary data from being stored in the storage space by discarding the sensor data of the seat position corresponding to the lower rank than the preset rank, without storing the noise source derivation unit 130 . For example, the noise source deriving unit 130 may include a computing means such as a microprocessor. Also, the noise source derivation unit 130 may include an interface capable of providing the derived noise source to a communication module that communicates with the control center.

The storage unit 140 stores the processing result of the noise source deriving unit 130 by the noise source deriving unit 130 . For example, the storage unit 140 may store the noise source data derived by the noise source deriving unit 130 . The storage unit 140 includes, for example, magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, and magnetic such as floppy disks. - It may include a computer-readable recording medium, such as a hardware device specially configured to store and execute program instructions, such as a magneto-optical media and a flash memory.

2 and 3 are flowcharts for explaining a method for deriving a noise source in an aircraft according to an embodiment of the present invention. It is a flowchart illustrating a process of deriving a noise source by the noise source deriving unit 130 .

Hereinafter, a method of deriving a noise source performed by the apparatus 100 for deriving a noise source according to an embodiment of the present invention will be described in detail with reference to FIGS. 1 to 5 .

In order to stably control and operate the vehicle, or for the vehicle itself to fly stably, it is necessary to be able to understand factors such as position, altitude, speed, direction, and obstacles. Accordingly, sensors such as GPS, accelerometer, magnetometer, barometer, distance meter, gyro sensor and inertial meter are mounted on the aircraft, and a sensor for measuring RPM corresponding to each motor is mounted to check the state of the motor.

The data collection unit 110 of the noise source deriving device 100 collects sensor data from at least one of various sensors mounted on the aircraft, and provides the collected sensor data to the data selection unit 120 ( S210 ).

Then, the data selection unit 120 selects sensor data of at least one field among a plurality of fields included in the sensor data collected by the data collection unit 110 and provides it to the noise source derivation unit 130 . However, among a plurality of fields included in various sensor data, there are fields that frequently change with time, but there are also fields that hardly change with time. In order to derive a noise source that is a source of an unpredictable number, it is necessary to classify such data in the data selector 120 because data that frequently changes over time is required.

Table 1 shows fields and data types constituting GPS data in GPGGA format.

GPGGA field data type variable or not One Sentence ID GPS type ID unchanged 2 UTC Time hhmmss.sss Seconds mostly change 3 Latitude ddmm.mmmm Minutes vary mainly 4 N/S Indicator N = North, S = South almost unchanged 5 Longitude dddmm.mmmm Minutes vary mainly 6 E/W Indicator E = East, W = West almost unchanged 7 Position Fix 0 = Invalid, 1 = Valid, 2 = Valid DGPS almost unchanged 8 Satellites Used Number of satellites in use (0-12) change every time 9 HDOP satellite error change every time 10 Altitude average sea level change every time 11 Altitude Units sea level unit unchanged 12 Geoid Separation Altitude difference between MSL and Geoid change every time 13 Separation Units altitude difference unit unchanged 14 DGPS Age DGPS unit unchanged 15 DGPS Station ID DGPS Enabled ID almost unchanged 16 checksum checksum change every time example $GPGGA,215235.670,3735.0064,N,12701.6746,E,1,03,50.0,0.0,M,19.6,M,0.0,0000*4F

Looking at Table 1, some fields change data over time, but some fields do not change or hardly change data over time. Accordingly, the data selector 120 selects a field in which data is changed according to the passage of time among GPS data in the GPGGA format and provides it to the noise source deriving unit 130 . For example, the noise source derivation unit ( 130) can be provided.

Table 2 shows fields and data types constituting GPS data in GPRMC format.

GPRMC field data type variable or not One Sentence ID GPS type ID unchanged 2 UTC Time hhmmss.sss Seconds mostly change 3 Status A = Valid, V, Invalid almost unchanged 4 Latitude ddmm.mmmm Minutes vary mainly 5 N/S Indicator N = North, S = South almost unchanged 6 Longitude dddmm.mmmm Minutes vary mainly 7 E/W Indicator E = East, W = West almost unchanged 8 speed over ground Unit: knots change every time 9 Course over ground Unit: Degrees change every time 10 UTC Date DDMMYY almost unchanged 11 Magnetic variation Unit: Degrees change every time 12 checksum change every time example $GPRMC,215235.670,A,3735.0064,N,12701.6746,E,0.000000,,060905,,*12

Looking at Table 2, some fields change data over time, but some fields do not change or hardly change data over time. Accordingly, the data selector 120 selects a field in which data is changed according to the passage of time among GPS data in the GPRMC format and provides it to the noise source deriving unit 130 . For example, the data selector 120 may include sensor data of at least one of a UTC time field, a latitude field, a longitude field, a speed over ground field, a course over ground field, a magnetic variation field, and a checksum field among GPS data in the GPRMC format. may be selected and provided to the noise source deriving unit 130 .

Table 3 shows fields and data types constituting GPS data in GPGSV format.

GPGSV field data type variable or not One Sentence ID GPS type ID unchanged 2 Number of messages Number of messages to receive (1-3) almost unchanged 3 sequence number Message number (1-3) almost unchanged 4 Satellites in view number of receivable satellites almost unchanged 5 Satellite ID 1 (1-32) Satellite information changes for each message 6 Elevation 1 Altitude of the satellite (0-90) Satellite information changes for each message 7 Azimuth 1 Azimuth of the satellite (0-359) Satellite information changes for each message 8 SNR 1 Signal-to-noise ratio (0-99) change every time 9 Satellite ID 2 (1-32) Satellite information changes for each message 10 Elevation 2 Altitude of the satellite (0-90) Satellite information changes for each message 11 Azimuth 2 Azimuth of the satellite (0-359) Satellite information changes for each message 12 SNR 2 Signal-to-noise ratio (0-99) change every time 13 Satellite ID 3 (1-32) Satellite information changes for each message 14 Elevation 3 Altitude of the satellite (0-90) Satellite information changes for each message 15 Azimuth 3 Azimuth of the satellite (0-359) Satellite information changes for each message 16 SNR 3 Signal-to-noise ratio (0-99) change every time 17 Satellite ID 4 (1-32) Satellite information changes for each message 18 Elevation 4 Altitude of the satellite (0-90) Satellite information changes for each message 19 Azimuth 4 Azimuth of the satellite (0-359) Satellite information changes for each message 20 SNR 4 Signal-to-noise ratio (0-99) change every time 21 checksum change every time example $GPGSV,3,2,10,13,34,279,00,23,33,236,00,15,29,076,40,25,25,143,38*71

Looking at Table 3, in some fields, data changes over time, but in some fields, data does not change or hardly changes over time. Also, some fields change for each message, but since satellite information is changed, it may be inappropriate to use as a noise source source. Accordingly, the data selector 120 selects a field in which data is changed according to the passage of time among GPS data in the GPGSV format and provides it to the noise source deriving unit 130 . For example, the data selection unit 120 selects sensor data of at least one of the SNR 1 field, the SNR 2 field, the SNR 3 field, the SNR 4 field, and the Checksum field from among the GPS data of the GPGSV format to select the noise source deriving unit 130 . ) can be provided.

The sensor data of the accelerometer consists of three directions, respectively, the X-axis, Y-axis, and Z-axis. As a sensor that detects the speed, position, inclination, and direction change of the vehicle, independent data is output for each direction, so all three types of data can be used as a noise source. Accordingly, the data selection unit 120 may select all fields of the accelerometer sensor data and provide it to the noise source derivation unit 130 .

The sensor data of the gyro sensor, like the sensor data of the accelerometer, consists of three directions: X, Y, and Z. It converts the Coriolis force generated when the aircraft rotates into an electrical signal. Also, since independent data is output in each direction, all three types of data can be used as noise source sources. Accordingly, the data selection unit 120 may select all fields of the gyro sensor data and provide it to the noise source derivation unit 130 .

A magnetometer sensor is a sensor that detects the magnetic field emitted from the earth, and the direction and strength can be derived from it. It is also configured in three directions, X-axis, Y-axis, and Z-axis, and can vary greatly depending on the flight method, position, and speed of the aircraft. Accordingly, the data selection unit 120 may select all fields of the magnetometer sensor data and provide it to the noise source derivation unit 130 .

In addition, various sensors may be added to the vehicle according to the purpose of the vehicle, such as a barometer, a range finder, a gyro sensor (maintaining level), an inertial meter, motor RPM, and the like. In the case of a vehicle that collects environmental data, the air pressure may vary depending on the day or time of flight, and the distance detected from the vehicle may vary depending on the region. In addition, in the case of an aircraft, it has at least four motors for propellers for flight. At this time, since the RPM of each motor is different according to the direction, speed, and altitude that the aircraft wants to go, all these data can be adopted as a source of irregularity, and the data selection unit 120 sets all data as a source of irregularity. It may be selected as a source and provided to the noise source derivation unit 130 (S220).

Figure 4 is an exemplary view of sensor data by the MPU6050 module that can be mounted on the vehicle. The MPU6050 module is equipped with acceleration, gyro, and temperature sensors that are essential for flight. It outputs a total of 7 data, 3 axes of acceleration, 3 axes of gyro, and temperature. The data format consists of 2-bytes for each field, making a total of 14-bytes. For example, the data selection unit 120 may select all fields as irregular source sources for the sensor data of the MPU6050 module and provide them to the noise source derivation unit 130 .

The noise source deriving unit 130 derives at least a portion of the sensor data selected by the data selecting unit 120 as a noise source (S230).

Even if some fields of the GPS data shown in Tables 1 to 3 are selected as the source source for the noise source by the data selection unit 120, since only the position of some of the plurality of digits is changed, a separate derivation process must be performed. For example, in the UTC Time field of GPS data of the GPGGA format, it is necessary to derive only the second unit as a noise source because the unit of second is mainly changed.

5 is an example of a noise source that the noise source deriving apparatus 100 according to an embodiment of the present invention can derive from sensor data, and shows sequentially increasing time data.

The noise source derivation unit 130 may select at least one digit position based on a width that varies with respect to a plurality of digits, and derive a plurality of sensor data according to the passage of time of the selected digit position as a noise source. In this case, the noise source derivation unit 130 may give a change rate ranking for each seat position based on the varying width for a plurality of digits ( S310 ), and may derive the noise source based on the change rate ranking. In this case, the noise source derivation unit 130 may discard the sensor data of the seat position with the low change rate rank without storing (S320), and derive the sensor data of the seat position with the high change rate order as the noise source (S330). For example, the noise source derivation unit 130 may calculate a change amount score for each seat position as an entropy value of the entropy evaluation tool, and may give a change rate ranking according to the change amount score. A process of deriving a noise source by the noise source deriving unit 130 will be described through the example of FIG. 5 .

-byte를 수집하고, 도출부(130)는

-byte만 채택하여 도출할 수 있다. 도 5의 예시에서는 4-byte 중 2-byte만 채택할 수 있다. 화살표 왼쪽에 묶음으로 표시한 바와 같이 2-byte만 채택하고, 자리 위치(index)를 0번부터 3번까지 부여할 수 있다. 화살표 오른쪽은 종 방향으로 나열되어 있던 데이터를 횡 방향으로 재배열한 것을 나타낸다. 2번 자리 위치와 3번 자리 위치의 데이터는 중복되는 값이 여러 번 나오므로 변화량 점수가 0번 자리 위치 및 1번 자리 위치보다 낮게 산출되고, 0번 자리 위치와 1번 자리 위치의 데이터는 중복되는 값이 적게 나오므로 변화량 점수가 2번 자리 위치 및 3번 자리 위치보다 높게 산출된다. 이 경우에, 잡음원 도출부(130)는 0번 자리 위치와 1번 자리 위치는 잡음원으로서 도출하여 저장부(140)에 저장하되 2번 자리 위치와 3번 자리 위치는 저장부(140)에 저장하지 않고 버려서 저장부(140)의 저장 공간에 불필요한 데이터가 저장되는 것을 방지할 수 있다. 예를 들어, 잡음원 도출부(130)는 산출된 변화량 점수에 기초하여 변화율 순위가 기 설정된 순위보다 낮은 순위에 해당하는 자리 위치의 센서 데이터를 저장하지 않고 버릴 수 있다.In the case of firmware composing the aircraft, storage space is relatively insufficient, unlike IT environments such as PCs, servers, or control centers. Accordingly, the data collection unit 110

- byte is collected, and the derivation unit 130 is

It can be derived by adopting only -byte. In the example of FIG. 5 , only 2-byte among 4-bytes can be adopted. As indicated by a bundle to the left of the arrow, only 2-bytes are adopted, and indexes from 0 to 3 can be assigned. The right arrow indicates that the data arranged in the vertical direction is rearranged in the horizontal direction. Since the data of the 2nd and 3rd positions have overlapping values multiple times, the variance score is calculated lower than that of the 0th and 1st positions, and the data of the 0th and 1st positions are duplicated. Since there are fewer values, the variance score is calculated to be higher than the 2nd and 3rd digit positions. In this case, the noise source deriving unit 130 derives the 0th digit position and the 1st digit position as noise sources and stores them in the storage unit 140 , but the 2nd digit position and the 3rd digit position are stored in the storage unit 140 . It is possible to prevent unnecessary data from being stored in the storage space of the storage unit 140 by throwing it away. For example, the noise source derivation unit 130 may discard, without storing, sensor data of a seat position corresponding to a lower rank than a preset rank based on the calculated variation score.

The data collection unit 110, the data selection unit 120, and the noise source derivation unit 130 included in the noise source deriving device 100 in the vehicle according to an embodiment of the present invention may be configured by one or two or more processors. In addition, each step included in the method of deriving a noise source in an aircraft may be performed by a processor.

As described so far, according to the embodiment of the present invention, it is possible to derive noise sources, which are sources of unpredictable numbers, from various sensor data of the vehicle. Accordingly, even in an environment in which the control center cannot provide a noise source to the vehicle, it is possible to derive a noise source that the vehicle can use for safe communication, so that safe communication between the vehicle and the control center can be performed.

Combinations of each block in the block diagram attached to the present invention and each step in the flowchart may be performed by computer program instructions. These computer program instructions may be embodied in a processor of a general-purpose computer, special purpose computer, or other programmable data processing equipment, such that the instructions executed by the processor of the computer or other programmable data processing equipment may be configured in the respective blocks of the block diagram or of the flowchart. Each step creates a means for performing the described functions. These computer program instructions may also be stored in a computer-usable or computer-readable medium that may direct a computer or other programmable data processing equipment to implement a function in a particular manner, and thus the computer-usable or computer-readable medium. The instructions stored in the recording medium are also capable of producing a manufactured item containing instruction means for performing a function described in each block of the block diagram or each step of the flowchart. The computer program instructions may also be mounted on a computer or other programmable data processing equipment, such that a series of operational steps are performed on the computer or other programmable data processing equipment to create a computer-executed process to create a computer or other programmable data processing equipment. It is also possible that instructions for performing the processing equipment provide steps for carrying out the functions described in each block of the block diagram and in each step of the flowchart.

Further, each block or each step may represent a module, segment, or portion of code comprising one or more executable instructions for executing specified logical function(s). It should also be noted that in some alternative embodiments it is also possible for the functions recited in blocks or steps to occur out of order. For example, it is possible that two blocks or steps shown one after another may in fact be performed substantially simultaneously, or that the blocks or steps may sometimes be performed in the reverse order according to the corresponding function.

The above description is merely illustrative of the technical spirit of the present invention, and various modifications and variations will be possible without departing from the essential characteristics of the present invention by those skilled in the art to which the present invention pertains. Accordingly, the embodiments disclosed in the present invention are not intended to limit the technical spirit of the present invention, but to explain, and the scope of the technical spirit of the present invention is not limited by these embodiments. The protection scope of the present invention should be construed by the following claims, and all technical ideas within the equivalent scope should be construed as being included in the scope of the present invention.

100: noise source derivation device
110: data collection unit
120: data selection unit
130: noise source elicitation unit
140: storage

Claims (20)

delete delete A data collection unit that collects sensor data from the vehicle;
a data selection unit for selecting sensor data of at least one field among a plurality of fields included in the collected sensor data;
a noise source deriving unit deriving at least a portion of the selected sensor data as a noise source;
The data collection unit collects at least one data of GPS data, accelerometer data, gyro sensor data, magnetometer data, barometer data, distance measurement data, inertial data, and motor RPM data,
The GPS data is in GPGGA format,
The data selection unit selects sensor data of at least one of the UTC Time field, the Latitude field, the Longitude field, the Satellites Used field, the HDOP field, the Altitude field, the Geoid Separation field, and the Checksum field of the GPGGA format.
A device for deriving a noise source from an aircraft. A data collection unit that collects sensor data from the vehicle;
a data selection unit for selecting sensor data of at least one field among a plurality of fields included in the collected sensor data;
a noise source deriving unit deriving at least a portion of the selected sensor data as a noise source;
The data collection unit collects at least one data of GPS data, accelerometer data, gyro sensor data, magnetometer data, barometer data, distance measurement data, inertial data, and motor RPM data,
The GPS data is in GPRMC format,
The data selection unit selects sensor data of at least one of the UTC Time field, Latitude field, Longitude field, Speed over ground field, Course over ground field, Magnetic variation field, and Checksum field of the GPRMC format.
A device for deriving noise sources from a vehicle. A data collection unit that collects sensor data from the vehicle;
a data selection unit for selecting sensor data of at least one field among a plurality of fields included in the collected sensor data;
a noise source deriving unit deriving at least a portion of the selected sensor data as a noise source;
The data collection unit collects at least one data of GPS data, accelerometer data, gyro sensor data, magnetometer data, barometer data, distance measurement data, inertial data, and motor RPM data,
The GPS data is in GPGSV format,
The data selection unit selects sensor data of at least one of the SNR 1 field, the SNR 2 field, the SNR 3 field, the SNR 4 field, and the Checksum field of the GPGSV format.
A device for deriving a noise source from an aircraft. A data collection unit that collects sensor data from the vehicle;
a data selection unit for selecting sensor data of at least one field among a plurality of fields included in the collected sensor data;
a noise source deriving unit deriving at least a portion of the selected sensor data as a noise source;
The selected data has a plurality of digits,
The noise source derivation unit selects at least one digit position based on a width that varies with respect to the plurality of digits, and derives a plurality of sensor data according to the passage of time of the selected digit position as the noise source
A device for deriving noise sources from a vehicle. 7. The method of claim 6,
The noise source derivation unit is configured to assign a rate of change rank to each seat position based on a width that changes with respect to the plurality of digits, and derive the noise source based on the change rate rank.
A device for deriving a noise source from an aircraft. 8. The method of claim 7,
The noise source derivation unit calculates a change amount score for each position as an entropy value of an entropy evaluation tool, and assigns the change rate ranking according to the change amount score
A device for deriving a noise source from an aircraft. 8. The method of claim 7,
The noise source derivation unit discards the sensor data of the position corresponding to the lower rank than the preset rank without storing the change rate rank.
A device for deriving a noise source from an aircraft. delete delete As a noise source derivation method performed by a noise source derivation device in an aircraft,
collecting sensor data from the vehicle;
selecting sensor data of at least one field from among a plurality of fields included in the collected sensor data;
Deriving at least a portion of the selected sensor data as a noise source,
The collecting of the sensor data includes collecting at least one data of GPS data, accelerometer data, gyro sensor data, magnetometer data, barometer data, range finder data, gyroscope data, inertial data and motor RPM data,
The GPS data is in GPGGA format,
The step of selecting the sensor data includes at least one of the UTC Time field, Latitude field, Longitude field, Satellites Used field, HDOP field, Altitude field, Geoid Separation field, and Checksum field of the GPGGA format.
A method of deriving a noise source from a vehicle. As a noise source derivation method performed by a noise source derivation device in an aircraft,
collecting sensor data from the vehicle;
selecting sensor data of at least one field from among a plurality of fields included in the collected sensor data;
Deriving at least a portion of the selected sensor data as a noise source,
The collecting of the sensor data includes collecting at least one data of GPS data, accelerometer data, gyro sensor data, magnetometer data, barometer data, range finder data, gyroscope data, inertial data and motor RPM data,
The GPS data is in GPRMC format,
The step of selecting the sensor data includes selecting sensor data of at least one of the UTC Time field, Latitude field, Longitude field, Speed over ground field, Course over ground field, Magnetic variation field, and Checksum field of the GPRMC format.
A method of deriving a noise source from a vehicle. As a noise source derivation method performed by a noise source derivation device in an aircraft,
collecting sensor data from the vehicle;
selecting sensor data of at least one field from among a plurality of fields included in the collected sensor data;
Deriving at least a portion of the selected sensor data as a noise source,
The collecting of the sensor data includes collecting at least one data of GPS data, accelerometer data, gyro sensor data, magnetometer data, barometer data, range finder data, gyroscope data, inertial data and motor RPM data,
The GPS data is in GPGSV format,
The selecting of the sensor data may include selecting sensor data of at least one of the SNR 1 field, the SNR 2 field, the SNR 3 field, the SNR 4 field, and the Checksum field of the GPGSV format.
A method of deriving a noise source from a vehicle. As a noise source derivation method performed by a noise source derivation device in an aircraft,
collecting sensor data from the vehicle;
selecting sensor data of at least one field from among a plurality of fields included in the collected sensor data;
Deriving at least a portion of the selected sensor data as a noise source,
The selected data has a plurality of digits,
The deriving as the noise source includes selecting at least one digit position based on a width that varies with respect to the plurality of digits, and deriving a plurality of sensor data according to the passage of time of the selected digit position as the noise source.
A method of deriving a noise source from a vehicle. 16. The method of claim 15,
The deriving as the noise source may include assigning a rate of change rank to each seat position based on a width that varies with respect to the plurality of digits, and deriving the noise source based on the rank of change rate.
A method of deriving a noise source from a vehicle. 17. The method of claim 16,
The step of deriving as the noise source comprises calculating a change amount score for each position as an entropy value of an entropy evaluation tool, and assigning the change rate ranking according to the change amount score.
A method of deriving a noise source from a vehicle. 17. The method of claim 16,
In the step of deriving as the noise source, the sensor data of the position corresponding to the lower rank than the preset rank is discarded without storing the change rate rank.
A method of deriving a noise source from a vehicle. As a computer-readable recording medium storing a computer program,
The computer program, when executed by a processor,
As a noise source derivation method performed by a noise source derivation device in an aircraft,
collecting sensor data from the vehicle;
selecting sensor data of at least one field from among a plurality of fields included in the collected sensor data;
Deriving at least a portion of the selected sensor data as a noise source,
The selected data has a plurality of digits,
The step of deriving as the noise source may include selecting at least one digit position based on a width that varies with respect to the plurality of digits and deriving a plurality of sensor data according to time of the selected digit position as the noise source. A computer-readable recording medium containing instructions to be executed. As a computer program stored in a computer-readable recording medium,
The computer program, when executed by a processor,
As a noise source derivation method performed by a noise source derivation device in an aircraft,
collecting sensor data from the vehicle;
selecting sensor data of at least one field from among a plurality of fields included in the collected sensor data;
Deriving at least a portion of the selected sensor data as a noise source,
The selected data has a plurality of digits,
The step of deriving as the noise source may include selecting at least one digit position based on a width that varies with respect to the plurality of digits and deriving a plurality of sensor data according to time of the selected digit position as the noise source. A computer program comprising instructions to be executed.

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