KR101970240B1 - Onboard Monitoring Method and Apparatus for Ionospheric Threat Mitigation: Geometry Screening for Unmanned Aircraft System Applications - Google Patents

Abstract

The present invention relates to a global navigation satellite system (GNSS)-mounted satellite geometry discriminating method, which secures navigation safety by enabling a navigation user using a differential global positioning system (DGPS)-based system to calculate the maximum vertical position error that can occur due to ionospheric anomaly; and an apparatus using the same. To this end, in the present invention, a system with computational efficiency and flexibility is designed by operating a satellite geometry technique, which is operated in a ground device, in an unmanned aircraft-mounted navigation system. In a GBAS, only a CCD monitor is used. But, in an LAD-GNSS, DSIGMA is added, which takes the directionality into consideration during calculation process of the maximum pseudo-range error. Therefore, accurate pseudo-range error simulation is possible. In addition, by operating the satellite geometry discrimination technique in the unmanned aircraft-mounted navigation system, a mounted navigation device (user) knows the combination of satellite geometries used in positioning of the user such that a calculation process for many satellite combinations is not necessary, thereby rapidly discriminating the satellite geometry. An MIEV value is directly compared with an alarm threshold value to determine availability in an LAD-GNSS performed only for one satellite geometry, unlike in a GBAS which determines whether a subset of a specific satellite geometry is available through vertical protection level expansion, thereby rapidly performing navigation control of an unmanned aircraft.

Description

TECHNICAL FIELD [0001] The present invention relates to a method and an apparatus for satellite geometry discrimination using an unmanned aerial vehicle for mitigation of ionospheric threats,

The present invention relates to a Global Navigation Satellite System (GNSS) equipped with a Global Navigation Satellite System (GNSS), which allows a navigation user using a DGPS (Differential Global Positioning System) based system to calculate the maximum vertical position error that can occur due to an ionospheric anomaly, To a method and apparatus for satellite geometry.

Ground-Based Augmentation System (GBAS) is a system developed for the aircraft's precision airport approach and automatic landing by providing GNSS error correction information and integrity information to the user. If severe Ionospheric storms occur during operation of the system, the ionospheric delay value changes rapidly, and when the user of the reinforcement system uses the correction information when such ionospheric anomaly occurs, the accuracy of the user's position estimate is significantly degraded. Therefore, if the ionospheric anomalies falling within the category of the ionosphere threat model are not detected and notified in a timely manner through ground monitoring, the user may be in great danger. In response to these ionosphere threats, GBAS is working with code-carrier divergence (CCD) monitors and satellite geometry algorithms on terrestrial equipment.

LAD-GNSS (Local-Area Differential GNSS) is a GBAS system that reduces development costs and simplifies system complexity. It is a system proposed for safe navigation operation for UAVs. Since LAD-GNSS derives correction information from DGPS principles like GBAS, the system affected by ionospheric anomaly is the same as GBAS. In response to the ionospheric anomaly, LAD-GNSS introduced DSIGMA (Dual Solution Ionospheric Gradient Monitoring Algorithm) as well as CCD monitor and satellite geometry techniques operating in GBAS.

The common features and differences of the satellite meteorological techniques operating in GBAS and LAD-GNSS are as follows. First of all, the common point is that it monitors the maximum value of the vertical ionospheric position error that can occur when the ionospheric monitor can not detect it, and it is the final monitor considering the situation where the ionospheric anomaly is not detected. The difference is that in GBAS, only CCD monitors are used, but in LAD-GNSS DSIGMA is added.

KR 10-0980762 B1

In the existing GBAS, the driving subject of the satellite geometry classification technique was in the ground device. Since the terrestrial equipment does not know the combination of satellites that the nearby user actually uses for positioning, it should calculate the vertical position error for every possible number of satellite geometries in combination with the received satellites, It is a big problem in the field of unmanned aerial navigation. The present invention aims at designing a system which is designed to solve such a problem and operates a satellite geometry classification technique operated in a ground device in a navigation device mounted on an unmanned aerial vehicle, thereby ensuring calculation efficiency and flexibility.

In GBAS, only CCD monitor is used. In LAD-GNSS, DSIGMA considering directionality is added in calculation of maximum pseudorange error, so that more accurate pseudorange error simulation can be performed.

In addition, since the satellite geometry classification technique is operated in the navigation device mounted on the unmanned aerial vehicle, the navigation device (user) knows the combination of the satellite geometry used in the positioning, In LAD-GNSS, which is performed only for one satellite geometry, unlike in GBAS, which can discriminate satellite geometry and determine whether subsets of certain satellite geometries can be used through the expansion of vertical protection level, So that it is possible to quickly control the navigation of the unmanned airplane.

에 의해 산출될 수 있으며, 여기서 IEV_i는 i번째 위성의 수직 전리층 위치 오차, R은 전리층 기울기로 인해 발생할 수 있는 최대 의사거리 오차, S_v,i는 i번째 위성의 수직 위성 기하 계수이다.In order to accomplish the above object, there is provided a method for discriminating satellite geometry for mitigation of ionospheric threat by: (a) collecting parameters for calculating a maximum pseudorange error; ; (b) calculating a maximum pseudorange error from the parameter; (c) calculating a vertical ionospheric position error of each satellite; (d) determining a final vertical ionospheric position error value from the calculated vertical ionospheric position error of each satellite; And (e) determining whether the navigation system is available using the final vertical ionospheric position error value, wherein the vertical ionospheric position error of each satellite in step (c)

Where IEV _i is the vertical ionospheric position error of the i th satellite, R is the maximum pseudorange error that can be caused by the ionospheric slope, and S _{v, i} is the vertical satellite geometry factor of the i th satellite.

The parameters of steps (a) and (b) above may include variables having directionality.

The final vertical ionospheric position error value of the step (d) may be determined as a maximum value among the absolute values of the vertical ionospheric position errors of the calculated satellites.

The determination of availability of the navigation system of step (e) directly compares the positional error limit (hereinafter referred to as 'alarm limit') required in the area under operation of the UAV and the final vertical ionospheric position error value, It can be determined that the navigation system can be used when the vertical ionospheric position error is less than or equal to the alarm limit.

에 의해 산출될수 있으며, 여기서 IEV_i는 i번째 위성의 수직 전리층 위치 오차, R은 전리층 기울기로 인해 발생할 수 있는 최대 의사거리 오차, S_v,i는 i번째 위성의 수직 위성 기하 계수이다.According to another aspect of the present invention, there is provided an apparatus for discriminating satellite geometry mounted on an unmanned air vehicle, comprising: a maximum pseudo range error calculation parameter collector for collecting parameters for calculating a maximum pseudo range error; A maximum pseudorange error calculator for calculating a maximum pseudorange error from the parameter; A vertical ionospheric position error calculator for calculating a vertical ionospheric position error of each satellite and determining a final vertical ionospheric position error value; A navigation system availability determination unit for determining whether the navigation system is available using the final vertical ionospheric position error value; And a control unit for controlling the respective components of the satellite geometry separating apparatus mounted on the unmanned aerial vehicle to perform a series of processes related to satellite geometry,

Where IEV _i is the vertical ionospheric position error of the i th satellite, R is the maximum pseudorange error that can be caused by the ionospheric slope, and S _{v, i} is the vertical satellite geometry factor of the i th satellite.

delete

The parameter may include a variable having directionality.

The final vertical ionospheric position error value may be determined as a maximum value among the absolute values of the vertical ionospheric position error of each of the calculated satellites.

The determination of whether or not the navigation system is usable is made by directly comparing a position error limit (hereinafter referred to as an 'alarm limit') required in an operating area of the UAV and a final vertical ionospheric position error value, Is less than or equal to the alarm limit, it can be determined that the navigation system is usable.

According to the present invention, the present invention is devised to solve such a problem, and it is designed to design a system ensuring computation efficiency and flexibility by operating a satellite geometry classification technique operated on a ground device in an unmanned aerial vehicle navigation device , GBAS uses CCD monitor only, but DSADMA considering directionality is added in calculation of maximum pseudorange error in LAD-GNSS, so that more accurate pseudorange error simulation is possible.

In addition, since the satellite geometry classification technique is operated on the navigation device mounted on the unmanned aerial vehicle, the navigation device (user) knows the combination of the satellite geometries used in the positioning, , The LIE-GNSS, which is performed only for one satellite geometry, directly compares the MIEV value with the alarm threshold, unlike in the GBAS, which determines the availability of subsets of certain satellite geometries through the expansion of the vertical protection level Thereby making it possible to quickly control the navigation of the unmanned aerial vehicle.

Fig. 1 is a flow chart of simulating ionospheric pseudo range error calculation of GBAS.
2 is a diagram showing a situation in which an ionospheric pseudo range error calculation simulation parameter of LAD-GNSS (Local-Area Differential GNSS) of the present invention is applied.
Fig. 3 is a table showing the simulation range of the ionospheric pseudo range error calculation simulation parameter.
FIG. 4 shows an embodiment of a maximum pseudorange error result per scenario according to a UAV operating environment.
FIG. 5 is a flow chart of a satellite geometry separating apparatus equipped with an unmanned aerial vehicle of the LAD-GNSS performing the satellite geometry classification method of the present invention.
6 is a diagram showing a configuration of an unmanned aerial vehicle mounted satellite geometry separating apparatus.
FIG. 7 is a diagram showing a simulation result of maximum pseudo range error calculation in GBAS (a) and a simulation result of maximum pseudo distance error calculation (b) of LAD-GNSS of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, terms and words used in the present specification and claims should not be construed as limited to ordinary or dictionary terms, and the inventor should appropriately interpret the concepts of the terms appropriately It should be interpreted in accordance with the meaning and concept consistent with the technical idea of the present invention based on the principle that it can be defined. Therefore, the embodiments described in this specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention and do not represent all the technical ideas of the present invention. Therefore, It is to be understood that equivalents and modifications are possible.

Fig. 1 is a flow chart of simulating the calculation of the ionospheric pseudo range error of the GBAS.

A description of the satellite geometry classification technique of the existing GBAS is as follows. We calculate the maximum pseudorange error using the prior ionospheric threat simulation, and use this to calculate the vertical ionospheric position error. The description below is described in order.

First, the pseudo range error caused by the ionospheric slope is calculated as shown in the above figure. In GBAS, CSC (Carrier Smoothed Code) measurements, which are smoothed to mitigate signal noise, are used. In aircraft and ground stations, the difference between the measured values using the same time constant of 100 seconds is an error, and it is confirmed whether or not it is detected by the CCD monitor. Simulation of these scenarios is performed by simulating all the cases that can occur with the combination of variables, adjusting the size, width, moving speed, and initial position of the ionosphere slope, and then finding the maximum value for each Δv

Next, to calculate the vertical ionospheric position error, it is assumed that two satellites are simultaneously affected by the ionospheric slope in the worst ionospheric anomaly scenario. At this time, the vertical position error is expressed by the following equation.

IEV _{i, j} is the vertical ionospheric position error of the i and j satellites, and R is the maximum pseudorange error due to the ionospheric slope. It uses pre-simulated table values and is expressed as a function of the velocity of the ionosphere slope and the difference of the moving speed of the satellite, Δ v. S _{v, i} is the vertical satellite geometry factor of the i-th satellite and is a constant that translates to a position error region in the pseudorange error region.

The vertical satellite geometry factor is as follows.

(Elevation) and azimuth (Az, Azimuth) of the satellite, which are geometrical information, can be obtained by representing the position of the satellite in the NED (North, East, Down) coordinate system having the receiver position as a reference point. Using the elevation and azimuth angles of N satellites, we calculate the matrix G (size: N by 4) as shown in the following equation: Matrix G is a matrix containing distribution information of satellites and is a matrix that is necessarily calculated for GPS positioning calculation .

The matrix W (size: N by N) is a weighting matrix and consists of the variance of the pseudorange error probability distribution for each satellite.

The vertical satellite geometry factor is an element corresponding to the vertical component of the matrix S, which is a combination of the matrix G and the matrix W in the least squares method.

The largest value of IEVs derived from all possible satellite pairs obtained for a particular satellite geometry is defined as MIEV. When N satellites are observed from the GBAS terrestrial system at a specific point in time, they are generated from N to N-2 subsets of the satellite as shown in the following equation. One MIEV is calculated considering all satellite pairs per subset geometry.

The position error MIEV derived from the worst case ionospheric anomaly scenarios above should not exceed TEL. The TEL is derived from the Obstacle Clearance Surface (OCS) for precise access of the aircraft and is calculated to be 28.79 m at an exemplary crystal altitude of 200 ft. If the MIEV value exceeds the TEL value, the GBAS determines that a potential integrity threat exists.

GBAS expands the Vertical Position Level (VPL) to mitigate this potential integrity threat. The GBAS ground device determines the level of protection for all Subset satellite geometries at a specific point in time by:

K _ffmd is the coefficient of non-detection probability under the assumption that there is no measurement failure, and σ _i is the standard deviation of the error distribution for satellite i. The VPL _Ho derived from the above values is calculated for the subsets of all satellite geometries and compared with the pre-established vertical alarm limits. Subset geometries that exceed the vertical alarm limit are not approved for use by the GBAS ground system.

The statistical values used in the calculation of the vertical protection level are as follows: ground system error term, error term for the residual error related to the convection layer, error of the satellite's measurement value of the receiver in the aircraft, spatial resolution under the ionospheric static state and an error term for the residual error due to decorrelation.

The GBAS ground system expands the entire vertical protection level by multiplying the existing σ _vig by the expansion factor for all Subset geometries larger than the TEL value, that is, the Subset geometry, which MIEV determined to be a potential integrity threat in the worst ionosphere anomaly It has a value greater than the vertical alarm limit. We determine the I _vig that the vertical protection level is greater than the vertical alarm limit and broadcast the inflated integrity parameter. The aircraft will not allow the use of Subset geometry corresponding to the above condition (MIEV> TEL) by exceeding the vertical alarm limit calculated by the inflated use. In this way, it mitigates potential integrity threats that occur in the worst ionosphere anomaly scenarios.

2 is a diagram showing a situation in which an ionospheric pseudo range error calculation simulation parameter of LAD-GNSS (Local-Area Differential GNSS) of the present invention is applied.

Hereinafter, LAD-GNSS will be used as a term encompassing a GNSS-based unmanned aerial vehicle navigation system, that is, a ground station system and an unmanned aerial vehicle loading system.

In order to adapt the complexity of the existing GBAS satellite meteorological techniques described above to unmanned navigation systems, three major changes are applied as follows.

1. System architecture change from ground device to onboard navigation device

- Because the onboard navigation device (user) knows the combination of satellite geometry used at his location, no computational process is required for many satellite combinations.

2. Changing the worst ionospheric anomaly scenario

Unlike the scenario in the existing GBAS where two satellites are simultaneously affected by the ionospheric slope, LAD-GNSS defines that only one satellite is affected.

3. Direct comparison of MIEV and alarm limits, not vertical protection level expansion

- In LAD-GNSS, which is performed only for one satellite geometry, unlike in GBAS, which determines the availability of subsets of certain satellite geometries through the expansion of the vertical protection level, the MIEV value is directly compared with the alarm threshold to determine availability This makes it possible to control the navigation on the unmanned aerial vehicle more rapidly.

The following is a description of a simplified satellite LAD-GNSS satellite metric classification algorithm. First, as in GBAS, it calculates the maximum undetected pseudorange error on the monitor based on the simulation in advance.

2 is a diagram showing parameters of the pseudorange error simulation. Unlike simulation in GBAS, which does not consider directionality, LAD-GNSS with DSIGMA affected by directionality additionally includes simulation parameters such as direction angle of ground station, moving direction of slope, and moving direction of UAV.

FIG. 3 is a table showing a simulation range of the ionospheric pseudo range error calculation parameter, and FIG. 4 is an example of a maximum pseudorange error result per scenario according to the UAV operating environment.

The table in FIG. 3 shows the minimum and maximum values and the interval therebetween, which are the irradiation ranges set for each parameter. The variable ΔW, which is not shown in FIG. 2, represents the relative distance between the UAV and the ionosphere slope at the end of the simulation, and β represents the difference between the moving direction of the UAV and the moving direction of the ionospheric slope. An example of the maximum pseudorange error for the two scenarios with respect to the survey range of the table of FIG. 3 is shown in the table of FIG.

FIG. 5 is a flow chart of a satellite geometry division device 300 mounted on an LAD-GNSS unmanned aerial vehicle according to an embodiment of the present invention, FIG. 6 is a diagram illustrating a configuration of a satellite- FIG.

Hereinafter, a process for calculating the position error of the vertical ionosphere will be described with reference to FIGS. 5 and 6. FIG.

The pseudo range error refers to the error still remaining due to the ionosphere or the like even if the correction information received from the ground station is applied to the position information obtained from the navigation device mounted on the unmanned aerial vehicle.

First, the control unit 301 controls each module described below to perform a series of processes related to satellite geometry in the unmanned aerial vehicle mounted satellite geometric separator 300. The term "satellite geometry" means that the current location information of an unmanned aerial vehicle calculated by information from a navigation system, such as a navigation device on a unmanned aerial vehicle or a ground station, is judged to be correct.

The parameters are collected by the maximum pseudo distance error calculation parameter collecting unit 302 (S510). The parameters herein may include the direction angle of the ground station, the direction of movement of the slope, the moving direction of the UAV, and the like, which are parameters affected by the direction, as described above with reference to Fig. Other parameters that may be parameters are as described with reference to FIG. 2 and FIG.

From this, the maximum pseudo distance error calculator 303 calculates a maximum pseudo distance error (S520). The calculation of the maximum pseudo distance error may be performed in real time by calculation of the parameters (S520). However, the parameter table shown in FIG. 3 may be provided in the database 306 so that the maximum pseudorange error corresponding to the collected parameters In the database 306 (S520).

In LAD-GNSS, it is assumed that one satellite is affected by the ionospheric slope in the worst case scenario of ionospheric anomaly. At this time, the vertical position error is expressed by Equation 1, whereby the vertical ionospheric position error calculation unit 504 calculates the vertical ionospheric position error (S530).

IEV _i is the vertical ionospheric position error of the i-th satellite, and R is the maximum pseudorange error that can be caused by the ionospheric slope. It uses pre-simulated tabulated values. S _{v, i} is the vertical satellite geometry factor of the i-th satellite and is a constant that translates to a position error region in the pseudorange error region. This is because the element corresponding to the vertical component of S in Equation (1) is as described above.

Since the unmanned aerial vehicle (user) of LAD-GNSS knows its own satellite geometry, it does not need to obtain the ionospheric vertical position error for the subset of satellite geometry like GBAS. The vertical ionospheric position error calculator 304 selects the largest value (hereinafter referred to as 'MIEV') among the IEVs derived from all possible satellites obtained from the satellite geometry (S540).

When N satellites are observed from a GBAS terrestrial system at a particular point in time, MIEV is determined to be the largest of the N IEVs. The navigation system availability determination unit 305 determines whether a navigation system currently in operation (e.g., a navigation system) is in real-time, by directly comparing the MIEV value calculated in real time with a required position error limit (S550). If the navigation limit is exceeded, the navigation system is stopped to secure the user's safety from the ionosphere threat.

FIG. 7 is a diagram showing a simulation result of the maximum pseudo range error calculation in GBAS (a) and a simulation result of maximum pseudo distance error calculation (b) of LAD-GNSS of the present invention.

In FIG. 7 (a), the result of the maximum pseudo distance error calculation simulation performed in the existing GBAS is expressed as a relative speed as shown in the following figure. The blue line is the maximum value of the maximum pseudorange error calculated by the actual simulation, and the red line is a linearly modeled equation to facilitate the calculation. In actual operation, the red line value is used. As the relative speed approaches zero, it is difficult to detect the ionospheric slope on the CCD monitor operating in the GBAS ground station. Therefore, the maximum pseudorange error is generally maximum near zero.

In FIG. 7 (b), on the other hand, in the LAD-GNSS of the present invention, which is a simplified system for a UAV (unmanned aerial vehicle), it is assumed that a single satellite is affected by the ionospheric slope. Since the existing GBAS is a system supporting the maneuvering of manned airplanes, the worst-case scenarios were selected as the situation in which two satellites with little chance of occurrence were affected at the same time. However, in case of UAV, And to consider only the situation where only one satellite is affected to increase the availability and usability of the system.

In the scenario where one satellite is affected, there is no basis for determining the direction of the ionospheric slope as in the GBAS, so that the calculation of the positional error of the vertical ionosphere is performed for all directions. .

In Equation 2, s _{v, i} is a parameter determined according to the distribution of all satellites currently received irrespective of the direction of movement of the ionosphere slope. Therefore, the process of obtaining the maximum vertical ionospheric position error for all the moving directions is the same as the process for finding the maximum value of the maximum pseudorange error. That is, the worst case scenario is that the ionospheric slope is moving so as to have a relative velocity when the maximum pseudorange error has a maximum value. For this reason, LAD-GNSS uses the maximum pseudorange error as a constant model.

The following figure shows a graph of the maximum pseudo range error simulation produced by LAD-GNSS, where each color line is the maximum pseudorange error calculated on the size (g) of the ionospheric slope and the black line is the sum of all potential ionospheric threat ranges And the maximum pseudorange error model of the constant form calculated for the model. As with the GBAS, the closer the relative speed is to zero, the larger the pseudorange error is due to the difficulty in detecting the slope by the DSIGMA, which operates on the ground station and onboard equipment.

300: Unmanned aerial vehicle-mounted satellite geometry separator

Claims (10)

A satellite geomorphic device mounted on an unmanned aircraft is a method for discriminating satellite geometry for mitigation of ionospheric threats,
(a) collecting parameters for calculating a maximum pseudorange error;
(b) calculating a maximum pseudorange error from the parameter;
(c) calculating a vertical ionospheric position error of each satellite;
(d) determining a final vertical ionospheric position error value from the calculated vertical ionospheric position error of each satellite; And
(e) determining whether the navigation system is available using the final vertical ionospheric position error value
Lt; / RTI >
The vertical ionospheric position error of each satellite in step (c)

Lt; / RTI >
Where IEV _i is the vertical ionospheric position error of the ith satellite, R is the maximum pseudorange error that can be caused by the ionospheric slope, S _{v, i} is the vertical satellite geometry factor of the ith satellite,
Satellite geometry classification method. The method according to claim 1,
The parameters of steps (a) and (b)
Containing directional variables
Wherein the satellite is located at a predetermined position. delete The method according to claim 1,
The final vertical ionospheric position error value of step (d)
Which is determined as a maximum value among absolute values of the vertical ionospheric position error of each of the calculated satellites
Wherein the satellite is located at a predetermined position. The method according to claim 1,
The determination as to whether or not the navigation system of the step (e)
(Hereinafter, referred to as an 'alarm limit') and a final vertical ionospheric position error value in an area in which the UAV is operating, and when the final vertical ionospheric position error value is less than the alarm limit, What is judged to be usable
Wherein the satellite is located at a predetermined position. An apparatus for discriminating satellite geometry mounted on a UAV,
A maximum pseudorange error calculation parameter collector for collecting parameters for calculating maximum pseudorange error;
A maximum pseudorange error calculator for calculating a maximum pseudorange error from the parameter;
A vertical ionospheric position error calculator for calculating a vertical ionospheric position error of each satellite and determining a final vertical ionospheric position error value;
A navigation system availability determination unit for determining whether the navigation system is available using the final vertical ionospheric position error value; And
A controller for controlling each of the components of the satellite geometry separating device mounted on the UAV to perform a series of processes related to satellite geometry
Lt; / RTI >
The vertical ionospheric position error of each of the above-

Lt; / RTI >
Where IEV _i is the vertical ionospheric position error of the ith satellite, R is the maximum pseudorange error that can be caused by the ionospheric slope, S _{v, i} is the vertical satellite geometry factor of the ith satellite,
Unmanned airborne satellite geometry separator. The method of claim 6,
The parameter may comprise:
Containing directional variables
A satellite-based geomagnetic separation device with an unmanned aerial vehicle. delete The method of claim 6,
The final vertical ionospheric position error value is calculated by:
Which is determined as a maximum value among absolute values of the vertical ionospheric position error of each of the calculated satellites
A satellite-based geomagnetic separation device with an unmanned aerial vehicle. The method of claim 6,
The determination as to whether or not the navigation system is available,
(Hereinafter, referred to as an 'alarm limit') and a final vertical ionospheric position error value in an area in which the UAV is operating, and when the final vertical ionospheric position error value is less than the alarm limit, What is judged to be usable
A satellite-based geomagnetic separation device with an unmanned aerial vehicle.

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