CN111123307A - System and method for detecting dynamic performance of BDS user equipment - Google Patents

System and method for detecting dynamic performance of BDS user equipment Download PDF

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CN111123307A
CN111123307A CN201911343159.2A CN201911343159A CN111123307A CN 111123307 A CN111123307 A CN 111123307A CN 201911343159 A CN201911343159 A CN 201911343159A CN 111123307 A CN111123307 A CN 111123307A
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satellite
module
information
user equipment
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CN111123307B (en
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王琛琛
徐学永
周叶
冯灿
冯立清
施金金
李昌
黄浩
王俊凯
徐波
刘梦楠
赵西亭
张莹莹
惠孟堂
吴波
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North Information Control Institute Group Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/23—Testing, monitoring, correcting or calibrating of receiver elements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C23/00—Combined instruments indicating more than one navigational value, e.g. for aircraft; Combined measuring devices for measuring two or more variables of movement, e.g. distance, speed or acceleration
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
    • G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial

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  • Remote Sensing (AREA)
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  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Automation & Control Theory (AREA)
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Abstract

The invention belongs to the field of satellite detection, and particularly relates to a system and a method for detecting dynamic performance of BDS user equipment. The method comprises the following steps: BDS user equipment to be detected; a test reference module: the system is used for acquiring reference position, speed and attitude information; a vehicle-mounted platform: a carrying platform for the whole system; testing the user equipment access module: a double-antenna mode is adopted to provide signal access for a test reference module and BDS user equipment to be detected; a monitoring module; the test control and evaluation module: the device is connected with the user equipment, the test benchmark module and the signal acquisition, playback and monitoring module and used for setting and management of the test benchmark module and the user equipment, receiving, storing, analyzing and processing of test data, real-time display of test results, abnormal alarm, real-time plotting of a test driving route on a map, generation of a test recording table and post-analysis of the test data. The system has the advantages of strong detection reference adaptability, high precision, strong automation capability, good visualization effect, complete functions and the like.

Description

System and method for detecting dynamic performance of BDS user equipment
Technical Field
The invention belongs to the field of satellite detection, and particularly relates to a system and a method for detecting dynamic performance of BDS user equipment.
Background
The Beidou Satellite Navigation System (BDS) is a Satellite Navigation System which is independently constructed and independently operated in China and can provide all-weather, all-time and high-precision positioning, Navigation and time service for global users. And by 12 and 27 months in 2018, the Beidou No. three basic system is built and starts to provide global services. At present, the Beidou global service performance is as follows: the positioning accuracy is 10 meters in level and 10 meters in elevation, the speed measurement accuracy is 0.2 meter per second, and the service availability of the system is better than 95%. In the Asia-Pacific region, the positioning accuracy is 5 meters horizontally and 5 meters vertically. With the development of the construction and service capability of the Beidou satellite navigation system, the related BDS user equipment is widely applied to the fields of traffic transportation, navigation and ocean fishery, hydrological monitoring, weather forecasting, communication time system and the like, and gradually permeates the aspects of human social production and people life.
For BDS user equipment, dynamic performance is a key technical indicator to measure its performance. At present, scholars at home and abroad make relevant research on GNSS dynamic performance detection, mainly how to establish a proper dynamic detection reference, and provide different testing methods and detection systems, such as checking the dynamic performance of a receiver by using a linear rail coordinate, calculating the position as a reference in the dynamic operation process by using a stable operation track of an antenna phase center, evaluating the performance of dynamic positioning, solving the geometric distance of each epoch by using a detection method based on a double-antenna method, comparing the geometric distance with the accurate distance measured on the ground, and the like so as to check the dynamic positioning accuracy of a detection terminal; still other researchers have proposed detection methods using optical principle assistance, simulator simulation, etc. The methods have the problems of geometric locus calibration error, single motion locus, unified time system and coordinate system, incapability of recovering test scenes and the like, all adopt a test data post-processing mode, cannot inform abnormal conditions in the test in time, and have uncontrollable test process, poor visualization effect and low test efficiency.
Disclosure of Invention
The invention aims to provide a system and a method for detecting dynamic performance of BDS user equipment.
The technical solution for realizing the purpose of the invention is as follows: a system for detecting BDS user device dynamic performance, comprising:
BDS user equipment to be detected;
a test reference module: the system is used for acquiring reference position, speed and attitude information;
a vehicle-mounted platform: providing dynamic test conditions for a carrying platform of the whole system and a detection task;
testing the user equipment access module: a double-antenna mode is adopted to provide signal access for a test reference module and BDS user equipment to be detected;
a monitoring module: the system is used for recording the actual road conditions of the front, the left and the right and the surrounding scenes in the test;
the test control and evaluation module: the device is connected with the BDS user equipment to be detected, the test benchmark module, the signal acquisition playback module and the monitoring module and is used for setting management, receiving, storing, analyzing and processing test data, displaying the test result in real time, alarming abnormally, plotting the test driving route on a map in real time, generating a test record table and analyzing the test data afterwards of the test benchmark module and the BDS user equipment to be detected;
the power supply and distribution module: and supplying power to other modules.
Further, still include the signal acquisition playback module: and a full-band navigation signal acquisition playback instrument is adopted for completing the acquisition of satellite signals in the detection process.
Furthermore, the test reference module comprises a satellite signal acquisition submodule, a satellite signal enhancement information acquisition submodule, an inertia measurement unit and a wheel speed sensor.
Furthermore, the test user equipment access module comprises a signal receiving layer and a signal forwarding layer, wherein the signal receiving layer is used for receiving satellite signals, and the signal forwarding layer comprises a power divider and a matching cable and is used for forwarding and distributing signals received by the signal receiving layer; the signal receiving layer adopts a double-antenna mode and comprises a main GNSS antenna and a secondary GNSS antenna, wherein the main GNSS antenna is connected with the test reference module through one path of the forwarding layer, one path of the main GNSS antenna is connected with the satellite signal acquisition playback module, and the rest paths of the main GNSS antenna are connected with the BDS user equipment to be detected; the slave GNSS antenna is directly connected to the test reference module.
Furthermore, the monitoring module comprises a vehicle event data recorder, a bilateral camera, an internal panoramic camera, a hard disk video recorder, a storage hard disk and a ceiling type liquid crystal display;
the automobile data recorder is used for monitoring the condition of a road in front of the automobile, the two side cameras are used for monitoring the conditions of two sides of the road, the internal panoramic camera monitors the internal test process of the automobile, the hard disk video recorder and the storage hard disk complete video storage of monitoring videos, and the ceiling type liquid crystal display displays the monitoring videos.
A method for detecting dynamic performance of BDS user equipment by utilizing the system comprises the following steps:
step (1): the BDS user equipment to be detected uploads data to a test control and evaluation module in real time;
step (2): the test reference module adopts a self-adaptive method to obtain reference position information and provides a test comparison reference;
and (3): the test control and evaluation module completes the storage, analysis and evaluation of data and displays the result in real time.
Further, the method also comprises the following steps: step (4) the signal acquisition and playback module and the monitoring module finish the acquisition of satellite signals during testing, the recording of testing environment and the monitoring of testing process; and after the test is finished, the test control and evaluation module automatically generates a test report.
Further, the step (2) of obtaining the reference position information by the test reference module using an adaptive method specifically includes:
step (2-1): filtering, demodulating and decoding satellite signals of the main GNSS antenna and the auxiliary GNSS antenna acquired by the satellite signal acquisition submodule to acquire a satellite observation value and broadcast ephemeris information;
step (2-2): decoding and judging satellite enhancement information acquired by a satellite signal enhancement information acquisition submodule, and adaptively selecting an optimal positioning and orientation algorithm in the current state by combining the acquired observation value and broadcast ephemeris information to perform real-time position, orientation calculation and satellite signal quality parameter calculation;
step (2-3): processing the information collected by the inertial measurement unit and the wheel speed sensor to obtain position and speed information;
step (2-4): and judging according to the satellite signal quality parameters, and adaptively selecting an optimal integrated navigation algorithm suitable for the current state by combining the result of real-time satellite navigation calculation and the information obtained by the inertial measurement unit and the wheel speed sensor to perform integrated navigation calculation so as to obtain a real-time test reference.
Further, the step (2-2) is specifically as follows:
decoding the satellite enhancement information acquired by the satellite enhancement information acquisition submodule, judging the decoded telegraph text number according to a standard RTCM protocol, if the telegraph text number is the original observation data and the reference point position, determining the telegraph text number as the regional enhancement information, and if the telegraph text number is the satellite orbit, the clock error and the ionosphere correction information, determining the wide-area enhancement information
If the enhancement information only contains wide-area enhancement information, the real-time position is solved by combining the obtained observation value and the broadcast ephemeris information by adopting a real-time precise single-point positioning algorithm RTPPP, and an observation equation of the RTPPP is as follows:
Figure BDA0002332629060000031
Pi j(tr)＝ρ(ts,tr)+c(δtr-δts)+δPtrop+δPiono+δPmult+δPrel；
in the formula, trIs the time when the station receives the signal; t is tsIs the satellite carrier signal transmission time;
Figure BDA0002332629060000032
represents trThe carrier phase of the satellite j received by the time observation station i;
Figure BDA0002332629060000033
represents trSatellite j received by time station iOf a pseudo-range observation value, p (t)s,tr) Which is the geometric distance of the satellite to the receiver,
Figure BDA0002332629060000034
represents tRThe integer ambiguity of the satellite j observed on the observation station i at the moment; f. of0As reference frequency, δ tsIs tsClock difference of time, δ trIs trClock difference of time, delta phitropFor tropospheric errors, δ ΦionoIs ionospheric error, δ PmultFor multipath error, δ PrelIs the relativistic error, c is the speed of light;
in the calculation process, an ionosphere is corrected in an ionosphere-free combination mode, the wet component of the troposphere is estimated in real time, the dry component, the relativistic error and other errors of the troposphere are corrected based on a mature model, and the satellite position and the clock error are corrected based on a wide-area enhanced product;
if the enhancement information only contains regional enhancement information, firstly utilizing an observation value and broadcast ephemeris information to carry out pseudo-range single-point positioning solution to calculate an approximate position, then calculating the distance between the approximate position and a reference point position in a regional enhancement system, if the distance between the approximate position and the reference point position in the regional enhancement system is less than 15Km, adopting a common observation value double-difference algorithm to carry out position solution, and if the distance between the approximate position and the reference point position in the regional enhancement system is more than 15Km, adopting a common ionosphere-free combination algorithm to solve a real-;
if the enhancement information contains both regional enhancement information and wide-area enhancement information, firstly utilizing an observation value and broadcast ephemeris information to carry out pseudo-range single-point positioning solution to calculate a rough position, then calculating the distance between the rough position and a reference point position in a regional enhancement system, if the distance between the rough position and the reference point position in the regional enhancement system is less than or equal to 15Km, adopting a commonly-used observation value double-difference algorithm to carry out position solution, and if the distance between the rough position and the reference point position in the regional enhancement system is more than 15Km and less than 100Km, adopting a commonly-used ionosphere-; if the current time is more than 100Km, the satellite position is corrected in real time by using the orbit and clock correction of the wide area enhancement information while adopting an ionosphere-free combination algorithm, and then the real-time position is solved;
solving the azimuth angle and the pitch angle of the carrier by utilizing the carrier phases of the master GNSS antenna and the slave GNSS antenna and adopting a common carrier phase observation method based on double differences through coordinate conversion;
and obtaining an evaluation parameter of the satellite signal quality according to the observed value information and the variable of the position calculation process.
Further, the steps (2-4) are specifically as follows:
according to the satellite signal quality evaluation parameters obtained in the step (2-2), if the number of single epoch satellites is less than 4, or the PDOP is greater than 4, or the signal to noise ratio of the number of satellites exceeding 2/3 is less than 40, combining the result calculated in the step (2-3), and using a wheel speed sensor and an inertial measurement unit to solve the high-precision test reference position, speed and attitude in a speed combination mode, otherwise, combining the results in the step (2-2) and the step (2-3), and using a position, speed and attitude full combination mode to obtain the test reference information;
the wheel speed sensor and inertial measurement unit speed combined calculation method is as follows:
the state equation is:
Figure BDA0002332629060000041
in the formula, XINSThe state variable of the inertia measurement unit is specifically selected as follows:
Figure BDA0002332629060000051
δVE,δVN,δVUfor east, north and sky velocity errors of inertial navigation, delta phiE,δφN,δφUAttitude angle errors of east, north and sky directions, delta L, delta B and delta H are longitude, latitude and elevation errors, and delta omegaE,δωN,δωUThe gyroscope is arranged along the east direction,
The drift of the north direction and the sky direction,
Figure BDA0002332629060000052
zero bias for the accelerometer in the east, north and sky directions; xODAs state variables of wheel speed sensors, XOD＝WKAssuming a random constant that does not vary with time, F is the state matrix of the system, FINSThe state matrix of inertial navigation is W, the system noise vector is W, and the W is white noise with zero mean value and Q variance;
decomposing the speed measurement value of the wheel speed sensor into a navigation coordinate after error correction of a scale system, and comparing the navigation coordinate with the speed measurement value of inertial navigation to form an observation value of a Kalman filter; the measurement equation is as follows:
Z＝νINS-vOD＝HX+V
in the formula, V is measurement noise, the mean value is 0, the variance is white noise of R, and V isINSMeasurement speed of inertial navigation, vODThe speed measured by the wheel speed sensor.
The measurement matrix H is:
H＝[I3×3，M1，03×9，M2]
wherein the content of the first and second substances,
Figure BDA0002332629060000053
M2＝[-vODE,-vODN,-vODU]T,vODE,vODN,vODUcomponents of the speed tested by the wheel speed sensor in the east, north and sky directions of a navigation system are obtained;
solving an error value by using Kalman filtering according to the equation so as to obtain a test reference position, speed and posture;
the calculation method of the inertial measurement unit and the satellite navigation position, speed and attitude full combination mode is as follows:
the state equation is:
Figure BDA0002332629060000054
the measurement equation is as follows:
Figure BDA0002332629060000061
in the formula (I), the compound is shown in the specification,
Figure BDA0002332629060000062
LS，BS，HSlongitude, latitude and altitude, L, respectively, of inertial navigation measurementsBD，BBD，HBDLongitude, latitude and altitude, phi, respectively, of satellite navigation measurementsSN，φSUIs the component of attitude angle measured by inertial navigation in north direction and sky direction, phiBDN，φBDUComponent of attitude angle measured for satellite navigation in north direction, sky direction, vSE，vSN，vSUThe components of velocity measured by inertial navigation in the east, north and sky directions, vBDE，vBDN，vBDUThe components of velocity measured for satellite navigation in the east, north, and sky directions.
Compared with the prior art, the invention has the remarkable advantages that:
(1) the invention designs a method for self-adaptively obtaining the test reference, which can self-adaptively adjust to an optimal algorithm according to the actual test condition, thereby ensuring the precision of the test reference;
(2) the system of the application adopts the satellite acquisition playback instrument, can realize the acquisition and playback of satellite signals in the test process, is convenient for testers to test and recover satellite conditions afterwards, solves the problems in the traceability test and improves the detection efficiency;
(3) the system adopts the video monitoring module, can realize the recording and storage of the road conditions of the front, left and right directions of the running road of the vehicle in the test process and the monitoring of the test process, ensure the transparency of the test process and ensure the fairness of the test process;
(4) the detection system can display the test result in real time, plot the running track on a map in real time, have an abnormal alarm function and a mobile phone result checking function, facilitate the testers to check in time, solve the problems in the test and improve the detection efficiency;
(5) the detection system has the advantages of strong adaptability to test reference environment, high precision, strong automation capability, good visualization effect, complete functions and wider engineering application and popularization value.
Drawings
Fig. 1 is a schematic diagram of the system structure for detecting the dynamic performance of the BDS user equipment according to the present invention.
FIG. 2 is a flowchart illustrating the solving of the test benchmarking information of the test benchmarking module of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and examples.
Referring to fig. 1, a system for detecting dynamic performance of BDS user equipment includes a vehicle-mounted platform, a high-precision test reference module, a test user equipment access module, a power supply and distribution module, a signal acquisition playback module, a monitoring module, and a test control and evaluation module;
the vehicle-mounted platform is a medium-sized automobile in IVECO, is a carrying platform of the whole system and provides dynamic test conditions for detection tasks;
the testing user equipment access module provides a signal access mode for a testing reference module and BDS user equipment to be tested, and specifically comprises a signal receiving layer and a signal forwarding layer, wherein the signal receiving layer adopts a double-antenna mode and comprises a master GNSS antenna, a slave GNSS antenna and a power divider and a matched cable, the slave GNSS antenna is used for receiving satellite signals such as BDS (including Beidou satellite III), GPS and the like, the signal forwarding layer comprises a power divider and a matched cable and is used for forwarding and distributing signals received by the signal receiving layer, the power divider selects 1 to 8 paths, wherein one path of the master GNSS antenna is connected to the testing reference module through the forwarding layer, one path of the master GNSS antenna is connected to the satellite signal acquisition playback module, the other 6 paths of the master GNSS antenna are connected to the BDS user equipment to be tested, and;
the test reference module is connected with the test control and evaluation module and comprises a satellite signal acquisition submodule, a satellite signal enhancement information acquisition submodule, an inertia measurement unit (comprising a gyroscope and an accelerometer), a wheel speed sensor and the like, and the module obtains high-precision reference by adopting the following self-adaptive method according to the reference figure 2:
step one, filtering, demodulating and decoding satellite signals of a main GNSS antenna and a secondary GNSS antenna acquired by a satellite signal acquisition submodule to acquire a satellite observation value and broadcast ephemeris information;
decoding and judging satellite enhancement information acquired by a satellite signal enhancement information acquisition submodule, and adaptively selecting an optimal positioning and orientation algorithm in the current state by combining the acquired observation value and broadcast ephemeris information to perform real-time position and orientation calculation and satellite signal quality parameter calculation;
decoding the satellite enhancement information acquired by the satellite enhancement information acquisition submodule, judging the decoded telegraph text number according to a standard RTCM protocol, if the telegraph text number is the original observation data and the reference point position, determining the telegraph text number as the regional enhancement information, and if the telegraph text number is the satellite orbit, the clock error and the ionosphere correction information, determining the wide-area enhancement information.
If the enhancement information only contains wide-area enhancement information, the real-time position is solved by combining the obtained observation value and the broadcast ephemeris information by adopting a real-time precise point positioning algorithm (RTPPP), and an observation equation of the RTPPP is as follows:
Figure BDA0002332629060000081
Pi j(tr)＝ρ(ts,tr)+c(δtr-δts)+δPtrop+δPiono+δPmult+δPrel；
in the formula, trIs the time when the station receives the signal; t is tsIs the satellite carrier signal transmission time;
Figure BDA0002332629060000082
represents trThe carrier phase of the satellite j received by the time observation station i;represents trThe pseudorange observations, ρ (t), of the satellite j received at the time station is,tr) For satellite to receptionThe geometrical distance of the machine is determined,
Figure BDA0002332629060000084
represents tRThe integer ambiguity of the satellite j observed on the observation station i at the moment; f. of0As reference frequency, δ tsIs tsClock difference of time, δ trIs trClock difference of time, delta phitropFor tropospheric errors, δ ΦionoIs ionospheric error, δ PmultFor multipath error, δ PrelFor relativistic error, c is the speed of light. In the calculation process, an ionosphere is corrected in an ionosphere-free combination mode, the wet component of the troposphere is estimated in real time, the dry component, the relativistic error and other errors of the troposphere are corrected based on a mature model, and the satellite position and the clock error are corrected based on a wide-area enhanced product.
If the enhancement information only contains regional enhancement information, firstly using the observation value and the broadcast ephemeris information to carry out pseudo-range single-point positioning solution to calculate the approximate position, then calculating the distance between the approximate position and the reference point position in the regional enhancement system, if the distance between the approximate position and the reference point position in the regional enhancement system is less than 15Km, adopting a common observation value double difference algorithm to carry out position solution, and if the distance between the approximate position and the reference point position in the regional enhancement system is more than 15Km, adopting a common ionosphere-Free combination algorithm (Iono-Free combination) to solve the real-time.
If the enhancement information contains both regional enhancement information and wide-area enhancement information, firstly, pseudo-range single-point positioning is carried out by utilizing the observation value and the broadcast ephemeris information to calculate the approximate position, then the distance between the approximate position and the reference point position in the regional enhancement system is calculated, if the distance between the approximate position and the reference point position in the regional enhancement system is less than or equal to 15Km, the position is calculated by adopting a commonly-used observation value double-difference algorithm, and if the distance between the approximate position and the reference point position in the regional enhancement system is more than 15Km and less than 100Km, the real-time position is calculated by adopting a commonly-used. If the current time is more than 100Km, the satellite position is corrected in real time by using the orbit and clock correction of the wide area enhancement information while adopting the ionosphere-free combination algorithm, and then the real-time position is solved.
And solving the azimuth angle and the pitch angle of the carrier by utilizing the carrier phases of the master GNSS antenna and the slave GNSS antenna and adopting a common carrier phase observation method based on double differences through coordinate conversion.
And acquiring the evaluation parameters of satellite signal quality such as the real-time satellite number, the signal-to-noise ratio, the satellite geometric factors and the like of the satellite signal observation value according to the observation value information and the variables of the position calculation process.
Processing the information collected by the inertia measurement unit and the wheel speed sensor to obtain information such as position, speed and the like;
for data acquired by an inertial measurement unit, a common Runge-Kunta method is adopted to update four elements to solve position, speed and attitude information of inertial navigation, and speed information is acquired for a wheel speed sensor.
And step four, judging according to the satellite signal quality parameters, adaptively selecting an optimal combined navigation algorithm suitable for the current state by combining the real-time satellite navigation calculation result and the information obtained by the inertial measurement unit and the wheel speed sensor, performing combined navigation calculation, and further obtaining a real-time high-precision test reference.
According to the satellite signal quality evaluation parameters obtained in the step two, if the number of single epoch satellites is less than 4, or the PDOP is greater than 4, or the signal-to-noise ratio of the number of satellites exceeding 2/3 is less than 40, the high-precision test reference position, speed and attitude are solved by combining the results calculated in the step three and utilizing a speed combination mode by using a wheel speed sensor and an inertial measurement unit, or else, the test reference information is obtained by combining the results in the step two and the step three and utilizing a position, speed and attitude full combination mode.
1) The wheel speed sensor and inertial measurement unit speed combined calculation method is as follows:
the state equation is:
Figure BDA0002332629060000091
in the formula, XINSThe state variable of the inertia measurement unit is specifically selected as follows:
Figure BDA0002332629060000092
δVE,δVN,δVUfor east, north and sky velocity errors of inertial navigation, delta phiE,δφN,δφUThe attitude angle errors of the east direction, the north direction and the sky direction are delta L, delta B and delta H, and delta omega is longitude, latitude and elevation errorsE,δωN,δωUDrift of the gyroscope in the east, north and sky directions,
Figure BDA0002332629060000093
zero bias for the accelerometer in the east, north and sky directions. XODAs state variables of wheel speed sensors, XOD＝WKIt can be assumed to be a random constant that does not change with time, F is the state matrix of the system, FINSW is the state matrix of inertial navigation, and is the system noise vector, which is white noise with zero mean and Q variance.
And the speed measurement value of the wheel speed sensor is corrected by a scale system error and the like, then decomposed into navigation coordinates, and compared with the speed measurement value of inertial navigation to form an observation value of a Kalman filter. The measurement equation is as follows:
Z＝νINS-vOD＝HX+V
where V is measurement noise, mean 0, white noise with variance R, and V isINSIs the measurement speed, v, of inertial navigationODThe speed measured by the wheel speed sensor.
The measurement matrix H is:
H＝[I3×3，M1，03×9，M2]
wherein the content of the first and second substances,
Figure BDA0002332629060000101
M2＝[-vODE,-vODN,-vODU]T,vODE,vODN,vODUthe components of the velocity measured for the wheel speed sensor in the east, north, and sky directions of the navigation system.
And solving an error value by using Kalman filtering according to the equation so as to obtain a test reference position, speed and posture.
2) The calculation method of the inertial measurement unit and the satellite navigation position, speed and attitude full combination mode is as follows:
the state equation is:
Figure BDA0002332629060000102
the measurement equation is as follows:
Figure BDA0002332629060000103
in the formula (I), the compound is shown in the specification,
Figure BDA0002332629060000104
and estimating errors by adopting a common extended Kalman filtering method according to the equation to obtain the test reference coordinate.
The power supply and distribution module is connected with all other modules, comprises a digital power supply assembly, a UPS and a storage battery, adopts a driving generator to supply power, and is provided with a commercial power access port to supply power to all electronic equipment of the detection system;
the signal acquisition playback module is connected with the test control and evaluation module, and a full-band navigation signal acquisition playback instrument is adopted to complete the acquisition of satellite signals in the detection process, and the satellite condition in the test process is recovered afterwards, so that the data analysis afterwards is facilitated;
the monitoring module is connected with the test control and evaluation module and comprises a vehicle event data recorder, two-side cameras, an internal panoramic camera, a hard disk video recorder, a storage hard disk and a ceiling type liquid crystal display, wherein the vehicle event data recorder is used for monitoring the condition of a road in front of a vehicle, the two-side cameras are used for monitoring the condition of two sides of the road, the panoramic camera monitors the internal test process of the vehicle, the hard disk video recorder and the storage hard disk finish video recording and storage of monitoring videos, and the ceiling type liquid crystal display displays the monitoring videos;
the test control and evaluation module comprises a serial server, a network switch, an industrial personal computer, a KVM display and test evaluation software, and mainly completes the functions of setting management of high-precision reference equipment and BDS equipment to be tested, receiving, storing, analyzing and processing test data, real-time display of test results, abnormal alarm, real-time plotting of test driving routes on a map, generation of test recording tables, post-analysis of test data and the like.
The test user equipment access module and the power supply and distribution module provide access conditions for testing the BDS user equipment to be tested, and the test reference module provides a test comparison reference. After the BDS user equipment to be detected is accessed into the system, test data can be uploaded to the test control and evaluation module in real time, the test control and evaluation module completes storage, analysis and evaluation of the data, displays real-time results, gives an abnormal alarm and the like, a tester can check the real-time test results through a mobile phone or a display, and timely responds if the abnormal results occur. And meanwhile, the signal acquisition and playback module and the monitoring module finish the acquisition of satellite signals during testing, the recording of a testing environment and the monitoring of a testing process. After the test is finished, the test control and evaluation module can automatically generate a test report, and finally the detection of the dynamic performance of the BDS user equipment can be finished in a controllable and efficient manner.

Claims (10)

1. A system for detecting dynamic performance of a BDS user device, comprising:
BDS user equipment to be detected;
a test reference module: the system is used for acquiring reference position, speed and attitude information;
a vehicle-mounted platform: providing dynamic test conditions for a carrying platform of the whole system and a detection task;
testing the user equipment access module: a double-antenna mode is adopted to provide signal access for a test reference module and BDS user equipment to be detected;
a monitoring module: the system is used for recording the actual road conditions of the front, the left and the right and the surrounding scenes in the test;
the test control and evaluation module: the device is connected with the BDS user equipment to be detected, the test benchmark module, the signal acquisition playback module and the monitoring module and is used for setting management, receiving, storing, analyzing and processing test data, displaying the test result in real time, alarming abnormally, plotting the test driving route on a map in real time, generating a test record table and analyzing the test data afterwards of the test benchmark module and the BDS user equipment to be detected;
the power supply and distribution module: and supplying power to other modules.
2. The system of claim 1, further comprising a signal acquisition playback module: and a full-band navigation signal acquisition playback instrument is adopted for completing the acquisition of satellite signals in the detection process.
3. The system of claim 2, wherein the test reference module comprises a satellite signal acquisition sub-module, a satellite signal enhancement information acquisition sub-module, an inertial measurement unit, and a wheel speed sensor.
4. The system of claim 3, wherein the test user equipment access module comprises a signal receiving layer and a signal forwarding layer, the signal receiving layer is configured to receive a satellite signal, and the signal forwarding layer comprises a power splitter and a supporting cable, and is configured to forward and distribute a signal received by the signal receiving layer; the signal receiving layer adopts a double-antenna mode and comprises a main GNSS antenna and a secondary GNSS antenna, wherein the main GNSS antenna is connected with the test reference module through one path of the forwarding layer, one path of the main GNSS antenna is connected with the satellite signal acquisition playback module, and the rest paths of the main GNSS antenna are connected with the BDS user equipment to be detected; the slave GNSS antenna is directly connected to the test reference module.
5. The system of claim 4, wherein the monitoring module comprises a tachograph, a two-sided camera, an internal panoramic camera, a hard disk video recorder, and a storage hard disk and a top-mounted liquid crystal display;
the automobile data recorder is used for monitoring the condition of a road in front of the automobile, the two side cameras are used for monitoring the conditions of two sides of the road, the internal panoramic camera monitors the internal test process of the automobile, the hard disk video recorder and the storage hard disk complete video storage of monitoring videos, and the ceiling type liquid crystal display displays the monitoring videos.
6. A method of detecting dynamic performance of a BDS user device using the system of any of claims 1 to 5, comprising the steps of:
step (1): the BDS user equipment to be detected uploads data to a test control and evaluation module in real time;
step (2): the test reference module adopts a self-adaptive method to obtain reference position information and provides a test comparison reference;
and (3): the test control and evaluation module completes the storage, analysis and evaluation of data and displays the result in real time.
7. The method of claim 6, further comprising the steps of: step (4) the signal acquisition and playback module and the monitoring module finish the acquisition of satellite signals during testing, the recording of testing environment and the monitoring of testing process; and after the test is finished, the test control and evaluation module automatically generates a test report.
8. The method according to claim 6, wherein the step (2) of obtaining the reference information by the test reference module using an adaptive method specifically includes:
step (2-1): filtering, demodulating and decoding satellite signals of the main GNSS antenna and the auxiliary GNSS antenna acquired by the satellite signal acquisition submodule to acquire a satellite observation value and broadcast ephemeris information;
step (2-2): decoding and judging satellite enhancement information acquired by a satellite signal enhancement information acquisition submodule, and adaptively selecting an optimal positioning and orientation algorithm in the current state by combining the acquired observation value and broadcast ephemeris information to perform real-time position, orientation calculation and satellite signal quality parameter calculation;
step (2-3): processing the information collected by the inertial measurement unit and the wheel speed sensor to obtain position, speed and attitude information;
step (2-4): and judging according to the satellite signal quality parameters, and adaptively selecting an optimal integrated navigation algorithm suitable for the current state by combining the result of real-time satellite navigation calculation and the information obtained by the inertial measurement unit and the wheel speed sensor to perform integrated navigation calculation so as to obtain a real-time test reference.
9. The method according to claim 8, wherein the step (2-2) is specifically as follows:
decoding the satellite enhancement information acquired by the satellite enhancement information acquisition submodule, judging the decoded telegraph text number according to a standard RTCM protocol, if the telegraph text number is the original observation data and the reference point position, determining the telegraph text number as the regional enhancement information, and if the telegraph text number is the satellite orbit, the clock error and the ionosphere correction information, determining the wide-area enhancement information
If the enhancement information only contains wide-area enhancement information, the real-time position is solved by combining the obtained observation value and the broadcast ephemeris information by adopting a real-time precise single-point positioning algorithm RTPPP, and an observation equation of the RTPPP is as follows:
Figure FDA0002332629050000021
Pi j(tr)＝ρ(ts,tr)+c(δtr-δts)+δPtrop+δPiono+δPmult+δPrel；
in the formula, trIs the time when the station receives the signal; t is tsIs the satellite carrier signal transmission time;
Figure FDA0002332629050000031
represents trTime measuring stationi the carrier phase of the received satellite j; pi j(tr) Represents trThe pseudorange observations, ρ (t), of the satellite j received at the time station is,tr) Which is the geometric distance of the satellite to the receiver,
Figure FDA0002332629050000032
represents tRThe integer ambiguity of the satellite j observed on the observation station i at the moment; f. of0As reference frequency, δ tsIs tsClock difference of time, δ trIs trClock difference of time, delta phitropFor tropospheric errors, δ ΦionoIs ionospheric error, δ PmultFor multipath error, δ PrelIs the relativistic error, c is the speed of light;
in the calculation process, an ionosphere is corrected in an ionosphere-free combination mode, the wet component of the troposphere is estimated in real time, the dry component, the relativistic error and other errors of the troposphere are corrected based on a mature model, and the satellite position and the clock error are corrected based on a wide-area enhanced product;
if the enhancement information only contains regional enhancement information, firstly utilizing an observation value and broadcast ephemeris information to carry out pseudo-range single-point positioning solution to calculate an approximate position, then calculating the distance between the approximate position and a reference point position in a regional enhancement system, if the distance between the approximate position and the reference point position in the regional enhancement system is less than 15Km, adopting a common observation value double-difference algorithm to carry out position solution, and if the distance between the approximate position and the reference point position in the regional enhancement system is more than 15Km, adopting a common ionosphere-free combination algorithm to solve a real-;
if the enhancement information contains both regional enhancement information and wide-area enhancement information, firstly utilizing an observation value and broadcast ephemeris information to carry out pseudo-range single-point positioning solution to calculate a rough position, then calculating the distance between the rough position and a reference point position in a regional enhancement system, if the distance between the rough position and the reference point position in the regional enhancement system is less than or equal to 15Km, adopting a commonly-used observation value double-difference algorithm to carry out position solution, and if the distance between the rough position and the reference point position in the regional enhancement system is more than 15Km and less than 100Km, adopting a commonly-used ionosphere-; if the current time is more than 100Km, the satellite position is corrected in real time by using the orbit and clock correction of the wide area enhancement information while adopting an ionosphere-free combination algorithm, and then the real-time position is solved;
solving the azimuth angle and the pitch angle of the carrier by utilizing the carrier phases of the master GNSS antenna and the slave GNSS antenna and adopting a common carrier phase observation method based on double differences through coordinate conversion;
and obtaining an evaluation parameter of the satellite signal quality according to the observed value information and the variable of the position calculation process.
10. The method according to claim 9, wherein the steps (2-4) are as follows:
according to the satellite signal quality evaluation parameters obtained in the step (2-2), if the number of single epoch satellites is less than 4, or the PDOP is greater than 4, or the signal to noise ratio of the number of satellites exceeding 2/3 is less than 40, combining the result calculated in the step (2-3), and using a wheel speed sensor and an inertial measurement unit to solve the high-precision test reference position, speed and attitude in a speed combination mode, otherwise, combining the results in the step (2-2) and the step (2-3), and using a position, speed and attitude full combination mode to obtain test reference information;
the wheel speed sensor and inertial measurement unit speed combined calculation method is as follows:
the state equation is:
Figure FDA0002332629050000041
in the formula, XINSThe state variable of the inertia measurement unit is specifically selected as follows:
Figure FDA0002332629050000042
δVE,δVN,δVUfor east, north and sky velocity errors of inertial navigation, delta phiE,δφN,δφUAttitude angle errors of east, north and sky directions, delta L, delta B and delta H are longitude, latitude and elevation errors, and delta omegaE,δωN,δωUDrift of the gyroscope in the east, north and sky directions,
Figure FDA0002332629050000043
zero bias for the accelerometer in the east, north and sky directions; xODAs state variables of wheel speed sensors, XOD＝WKAssuming a random constant that does not vary with time, F is the state matrix of the system, FINSThe state matrix of inertial navigation is W, the system noise vector is W, and the W is white noise with zero mean value and Q variance;
decomposing the speed measurement value of the wheel speed sensor into a navigation coordinate after error correction of a scale system, and comparing the navigation coordinate with the speed measurement value of inertial navigation to form an observation value of a Kalman filter; the measurement equation is as follows:
Z＝νINS-vOD＝HX+V
in the formula, V is measurement noise, the mean value is 0, the variance is white noise of R, and V isINSMeasurement speed of inertial navigation, vODThe speed measured by the wheel speed sensor.
The measurement matrix H is:
H＝[I3×3，M1，03×9，M2]
wherein the content of the first and second substances,
Figure FDA0002332629050000044
M2＝[-νODE,-νODN,-νODU]T,νODE,νODN,νODUcomponents of the speed tested by the wheel speed sensor in the east, north and sky directions of a navigation system are obtained;
solving an error value by using Kalman filtering according to the equation so as to obtain a test reference position, speed and posture;
the calculation method of the inertial measurement unit and the satellite navigation position, speed and attitude full combination mode is as follows:
the state equation is:
Figure FDA0002332629050000051
the measurement equation is as follows:
Figure FDA0002332629050000052
in the formula (I), the compound is shown in the specification,
Figure FDA0002332629050000053
LS，BS，HSlongitude, latitude and altitude, L, respectively, of inertial navigation measurementsBD，BBD，HBDLongitude, latitude and altitude, phi, respectively, of satellite navigation measurementsSN，φSUIs the component of attitude angle measured by inertial navigation in north direction and sky direction, phiBDN，φBDUComponent of attitude angle measured for satellite navigation in north direction, sky direction, vSE，vSN，vSUThe components of velocity measured by inertial navigation in the east, north and sky directions, vBDE，vBDN，vBDUThe components of velocity measured for satellite navigation in the east, north, and sky directions.
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