CN115900796A - Positioning diagnosis method, device, equipment and storage medium - Google Patents
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Abstract
The invention relates to the field of data processing, and discloses a positioning diagnosis method, a positioning diagnosis device, positioning diagnosis equipment and a storage medium, wherein the method comprises the following steps: acquiring the acquired data of a plurality of sensors and fusing the acquired data of all the sensors to obtain a positioning state quantity; carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result; calculating the error between the collected data and the positioning state quantity; performing ambiguity diagnosis on the same state aiming at the acquired data to obtain an ambiguity diagnosis result; and judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result. According to the method, through processing of collected data and positioning state quantity, a sensor which changes according to the kinematics principle, a sensor and/or a positioning system with errors and/or a sensor or a positioning system which is ambiguous and aims at the same state and positions problems are determined, and positioning diagnosis of the sensor and the positioning system is achieved.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a method, an apparatus, a device, and a storage medium for location diagnosis.
Background
The positioning method of multi-sensor fusion is widely applied to the fields of automatic driving, robots, unmanned aerial vehicles and the like. And the state of each sensor in the fusion process determines the reliability and the precision of the final positioning result. The existing positioning system state evaluation method mainly calculates the difference between an estimated position and a real position as an index for evaluating the accuracy of a sensor. However, in most cases, the accuracy of the collected data collected by the sensors is difficult to judge, and especially in a large-scale motion scene such as vehicle driving, the accuracy and reliability of the collected data and further the sensors which have problems among the sensors are difficult to judge.
Disclosure of Invention
The invention mainly aims to solve the technical problem that the sensor with problems cannot be positioned in the existing positioning diagnosis process.
A first aspect of the present invention provides a localization diagnosis method, including: acquiring the acquired data of a plurality of sensors and fusing the acquired data of all the sensors to obtain a positioning state quantity; carrying out jump fault detection on the positioning state quantity based on the acquired data to obtain a jump detection result; calculating an error between the collected data and the positioning state quantity; performing ambiguity diagnosis on the same state aiming at the acquired data to obtain an ambiguity diagnosis result; and judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result.
Optionally, in a first implementation manner of the first aspect of the present invention, the acquiring data of a plurality of sensors and performing fusion processing on the acquired data of all the sensors to obtain a positioning state quantity includes: acquiring the acquisition data of a plurality of sensors at the current moment and the positioning state quantity of the sensors at the previous moment; inputting the positioning state quantity at the previous moment into a conversion function to obtain a first positioning state quantity at the current moment; and correcting the first positioning state quantity according to the acquired data at the current moment to obtain the positioning state quantity at the current moment.
Optionally, in a second implementation manner of the first aspect of the present invention, before the inputting the positioning state quantity at the previous time into the conversion function to obtain the first positioning state quantity at the current time, the method further includes: calculating a prediction deviation value and a Kalman gain matrix based on the positioning state quantity and the acquired data at the previous moment; updating the conversion function based on the predicted deviation value and the Kalman gain matrix.
Optionally, in a third implementation manner of the first aspect of the present invention, the performing, based on the collected data, a jump fault detection on the positioning state quantity to obtain a jump detection result includes: calling the collected data at the previous moment and the current moment and the positioning state quantity at the previous moment; calculating a second positioning state quantity based on the acquired data and the positioning state quantity at the previous moment; calculating to obtain the jumping quantity of the current moment based on the acquired data of the current moment and the second positioning state quantity; calculating a second-order determinant of the jump variable to obtain a jump judgment value at the current moment; determining whether a sensor corresponding to the jump judgment value is positioned as an abnormal based on the size of the jump judgment value; recording the sensor determined to be the abnormal location to a jump detection result.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the calculating the error includes mahalanobis distance and absolute error, and the calculating the error between the acquired data and the positioning state quantity includes: calculating the Mahalanobis distance and the absolute error of the acquired data at the current moment and the positioning state quantity at the current moment; determining whether a sensor or a positioning system corresponding to the mahalanobis distance and the absolute error is positioned as an abnormal location based on the magnitudes of the mahalanobis distance and the absolute error; and recording the abnormal positioning to an error.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the performing an ambiguous diagnosis on the same state for which the collected data is directed to obtain an ambiguous diagnosis result includes: calling the collected data aiming at the same state and collected at the current moment, wherein the collected data at least comprises first collected data and second collected data; calculating an absolute deviation and a direction deviation based on the first collected data and the second collected data; determining whether a difference of sensors corresponding to the first collected data and the second collected data falls within an allowable range based on magnitudes of the absolute deviation and the directional deviation; and if not, taking the sensors corresponding to the first collected data and the second collected data as abnormal positions and recording the abnormal positions to an ambiguity diagnosis result.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the determining, based on the jump detection result, the error, and the ambiguity diagnosis result, an abnormal location existing in the positioning system includes: respectively obtaining abnormal positioning in judgment results, wherein the judgment results comprise the detection results based on the jump, the errors and ambiguity diagnosis results; judging whether consistent items exist in the jump detection result, the error and the abnormal positioning in the ambiguity diagnosis result or not; if so, excluding the abnormal positioning only existing in the error and the ambiguity diagnosis result, and keeping the abnormal positioning appearing in the jump detection result; if not, removing the abnormal positioning of the repeated items recorded in the jump detection result, the error and the ambiguity diagnosis result and recording the abnormal positioning.
A second aspect of the present invention provides a localization diagnosis apparatus comprising: the acquisition data fusion module is used for acquiring the acquisition data of the sensors and fusing the acquisition data of all the sensors to obtain a positioning state quantity; the jump detection module is used for carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result; the error calculation module is used for calculating the error between the acquired data and the positioning state quantity; the ambiguity diagnosis module is used for carrying out ambiguity diagnosis on the same state aimed at by the acquired data to obtain an ambiguity diagnosis result; and the abnormal positioning judging module is used for judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result.
Optionally, in a first implementation manner of the second aspect of the present invention, the collected data fusion module is specifically configured to: the data acquisition unit is used for acquiring the current-time acquisition data and the last-time positioning state quantity of the plurality of sensors; the conversion unit is used for inputting the positioning state quantity at the previous moment into a conversion function to obtain a first positioning state quantity at the current moment; and the correction unit is used for correcting the first positioning state quantity according to the acquired data at the current moment to obtain the positioning state quantity at the current moment.
Optionally, in a second implementation manner of the second aspect of the present invention, the collected data fusion module further includes a conversion function updating unit, where the conversion function updating unit is specifically configured to: calculating a prediction deviation value and a Kalman gain matrix based on the positioning state quantity and the acquired data at the previous moment; updating the conversion function based on the predicted deviation value and the Kalman gain matrix.
Optionally, in a third implementation manner of the second aspect of the present invention, the hop detection module is specifically configured to: calling the collected data at the previous moment and the current moment and the positioning state quantity at the previous moment; calculating a second positioning state quantity based on the acquired data and the positioning state quantity at the previous moment; calculating to obtain the jumping quantity of the current moment based on the acquired data of the current moment and the second positioning state quantity; calculating a second-order determinant of the jump variable to obtain a jump judgment value at the current moment; determining whether a sensor corresponding to the jump judgment value is positioned as an abnormal based on the size of the jump judgment value; recording the sensor determined to be the abnormal location to a jump detection result.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the error calculation module is specifically configured to: calculating the Mahalanobis distance and the absolute error of the acquired data at the current moment and the positioning state quantity at the current moment; determining whether a sensor or a positioning system corresponding to the mahalanobis distance and the absolute error is positioned as an abnormal location based on the magnitudes of the mahalanobis distance and the absolute error; and recording the abnormal positioning to an error.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the ambiguity diagnosis module is specifically configured to: calling the collected data aiming at the same state and collected at the current moment, wherein the collected data at least comprises first collected data and second collected data; calculating an absolute deviation and a direction deviation based on the first collected data and the second collected data; determining whether a difference of sensors corresponding to the first collected data and the second collected data falls within an allowable range based on the magnitude of the absolute deviation and the direction deviation; if not, taking the sensor corresponding to the first collected data and the second collected data as abnormal location and recording the abnormal location to an ambiguity diagnosis result.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the abnormality positioning determining module is specifically configured to: respectively obtaining abnormal positioning in judgment results, wherein the judgment results comprise the jump detection result, the error and an ambiguity diagnosis result; judging whether consistent items exist in the jump detection result, the error and the abnormal positioning in the ambiguity diagnosis result or not; if so, excluding the abnormal positioning only existing in the error and the ambiguity diagnosis result, and keeping the abnormal positioning appearing in the jump detection result; and if not, removing the abnormal positioning of the repeated items recorded in the jump detection result, the error and the ambiguity diagnosis result and recording the abnormal positioning.
A third aspect of the present invention provides a positioning diagnostic apparatus comprising: a memory and at least one processor, the memory having requests stored therein, the memory and the at least one processor interconnected by a line; the at least one processor invokes the request in the memory to cause the location diagnostic device to perform the steps of the location diagnostic method described above.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein a request, which, when run on a computer, causes the computer to perform the steps of the above-described location diagnosis method.
According to the technical scheme, the method comprises the steps of acquiring the acquired data of a plurality of sensors and fusing the acquired data of all the sensors to obtain a positioning state quantity; carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result; calculating an error between the collected data and the positioning state quantity; performing ambiguity diagnosis on the same state of the acquired data to obtain an ambiguity diagnosis result; and judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result. According to the method, the positioning state quantity required by positioning at the current moment is estimated by fusing acquired data acquired by a sensor based on an extended Kalman filter, and then positioning diagnosis of the sensor and the positioning system is realized by determining the sensor which does not conform to the change of a kinematic principle, the sensor and/or the positioning system with errors and determining two sensors which have ambiguity and aim at the same state, searching a consistent item in the abnormal positioning of three results and positioning the sensor or the positioning system which has problems.
Drawings
FIG. 1 is a schematic diagram of a first embodiment of a location-based diagnostic method in an embodiment of the invention;
FIG. 2 is a schematic diagram of a second embodiment of the localization diagnosis method according to the embodiment of the present invention;
FIG. 3 is a schematic diagram of a third embodiment of the localization diagnosis method in the embodiment of the present invention;
FIG. 4 is a schematic diagram of an embodiment of a positioning diagnostic device in an embodiment of the invention;
FIG. 5 is a schematic diagram of another embodiment of a positioning diagnostic device in an embodiment of the invention;
fig. 6 is a schematic diagram of an embodiment of the positioning diagnosis device in the embodiment of the invention.
Detailed Description
According to the technical scheme, the method comprises the steps of acquiring the acquired data of a plurality of sensors and fusing the acquired data of all the sensors to obtain a positioning state quantity; carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result; calculating an error between the collected data and the positioning state quantity; performing ambiguity diagnosis on the same state of the acquired data to obtain an ambiguity diagnosis result; and judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result. According to the method, the positioning state quantity required by positioning at the current moment is estimated by fusing acquired data acquired by sensors based on a sensor of an extended Kalman filter, and then positioning diagnosis of the sensors and the positioning system is realized by determining the sensors which do not conform to the change of a kinematic principle, the sensors and/or the positioning system with errors and determining two sensors which have ambiguity and aim at the same state, searching for consistent items in the abnormal positioning of the three results, and positioning the sensors or the positioning system which have problems.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For ease of understanding, a specific flow of an embodiment of the present invention is described below, and referring to fig. 1, a first embodiment of a location-based diagnostic method in an embodiment of the present invention includes:
101. acquiring the acquired data of a plurality of sensors and fusing the acquired data of all the sensors to obtain a positioning state quantity;
in this embodiment, the plurality of sensors at least includes an IMU inertial measurement unit, a lidar, a global navigation satellite system GNSS, and a wheel odometer. The sensor data and the estimated positioning state quantity are in corresponding relation, namely, if any one of the data is acquired, the positioning state quantity corresponding to the acquired data exists. The positioning state quantity is a predicted value of data collected by the sensor.
Specifically, the positioning state quantity or the acquired data at least includes a position P, a velocity V, an attitude R, an IMU acceleration offset α, and an IMU angular velocity offset β of the subject. The covariance matrix of the state quantities is
And fusing the acquired data by adopting an extended Kalman filter to obtain a positioning state quantity corresponding to the acquired data.
102. Carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result;
in this embodiment, the positioning state quantity of the previous frame corresponding to the acquired data is subjected to jump fault detection by acquiring the acquired data of the current frame, whether the positioning state quantity has a jump fault is determined, and the abnormal positioning with the jump fault is recorded in a jump detection result.
Specifically, the IMU can measure the acceleration and angular velocity of the subject in a short time, and the moving velocity is one of the positioning state quantities of the positioning system. Predicting the current position according to the estimated speeds at the previous moment and the current moment and the position estimation result at the previous moment, estimating the deviation with the actual position estimation result, and judging whether jumping occurs or not; predicting the current attitude according to the angular speeds measured by the IMU at the previous moment and the current moment and the attitude estimation result at the previous moment, and then carrying out deviation estimation on the current attitude and the actual attitude estimation result to judge whether jump occurs or not; and predicting the speed of the current positioning according to the acceleration measured by the IMU at the previous moment and the current moment and the speed estimation result at the previous moment, and estimating the deviation with the actual speed estimation result to judge whether the jump occurs.
103. Calculating the error between the collected data and the positioning state quantity;
in the present embodiment, the errors between the collected data and the positioning state quantities include mahalanobis distance and absolute error.
Specifically, in the fusion positioning process based on the extended kalman filter, the mahalanobis distance and the absolute error between the position, the attitude, the positioning state quantity of the state and the acquired data of the sensor are calculated. When the Mahalanobis distance or the absolute error is larger than the set threshold, the positioning state quantity and the acquired data of the sensor have larger deviation, and one of the fusion positioning system or the sensor can be considered to have a fault, a fault diagnosis that the Mahalanobis distance or the absolute error is too large is sent out, or the sensor and the positioning system which exceed the threshold are recorded in the error.
104. Performing ambiguity diagnosis on the same state aiming at the acquired data to obtain an ambiguity diagnosis result;
in this embodiment, when different sensors have a large deviation from the collected data of the same state, it is considered that an ambiguity occurs between the sensors. At this point, a sensor ambiguous fault diagnosis should be sent, or an ambiguous sensor record and an ambiguous diagnosis result should be recorded.
105. And judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result.
In this embodiment, the abnormal positioning in which a fault may occur in the positioning system is determined by comparing and judging the abnormal positioning in which the jump detection result, the error and the ambiguity diagnosis result are recorded as abnormal positions, where the abnormal positioning is a sensor or a positioning system judged to have a fault.
In this embodiment, the collected data of a plurality of sensors is acquired and the collected data of all the sensors are subjected to fusion processing to obtain a positioning state quantity; carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result; calculating an error between the collected data and the positioning state quantity; performing ambiguity diagnosis on the same state of the acquired data to obtain an ambiguity diagnosis result; and judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result. According to the method, the positioning state quantity required by positioning at the current moment is estimated by fusing acquired data acquired by a sensor based on an extended Kalman filter, and then positioning diagnosis of the sensor and the positioning system is realized by determining the sensor which does not conform to the change of a kinematic principle, the sensor and/or the positioning system with errors and determining two sensors which have ambiguity and aim at the same state, searching a consistent item in the abnormal positioning of three results and positioning the sensor or the positioning system which has problems.
Referring to fig. 2, a second embodiment of the positioning diagnosis method according to the embodiment of the present invention includes:
201. acquiring the acquisition data of a plurality of sensors at the current moment and the positioning state quantity of the sensors at the previous moment;
in this embodiment, the acquired data of the sensor and the positioning state quantity at the previous time are divided into positions, speeds and states, so as to be used for correcting the positioning state quantity at the current time in the subsequent steps according to the positions, the speeds and the states.
202. Calculating a prediction deviation value and a Kalman gain matrix based on the positioning state quantity and the acquired data at the previous moment;
in the present embodiment, the positioning state quantity at the previous time is measured according to the acceleration and the angular velocity measured by the IMU sensor
Converted into the positioning status quantity at the current time>
The transformation function is f (X). The corner mark p represents the result of the current positioning state quantity after prediction, the corner mark c represents the result of the positioning state quantity after correction, the result is the final output of the system at each moment, n is the measurement noise of the IMU, and k is the current moment. The updating formula of the positioning state quantity and the covariance matrix is as follows:
in this embodiment, the ith sensor collects data as
The current positioning status quantity is->
An observation function of
Where n is the measurement noise of the sensor. Calculating the prediction deviation value between the solution positioning state quantity and the actual sensor acquisition data as follows:
in the present embodiment, it is preferred that,
the matrix is the observation function h of the ith sensor i (X) Jacobian matrix of state quantities in
The results of (a). Taking the correction procedure of a wheeled odometer as an example, a decision is made whether or not a decision is made>
Is the current status amount>
The speed of the vehicle is estimated in (1), the coordinate system is an IMU coordinate system, and the judgment result is based on the IMU coordinate system>
The coordinate system is the coordinate system of the wheel-type odometer. A rotational translation relationship exists between the IMU and the wheeled odometer>
The specific form of the above equation is:
measurement noise n c Has a covariance matrix of
An observation Kalman gain matrix may be evaluated>
Comprises the following steps:
203. updating the conversion function based on the prediction deviation value and the Kalman gain matrix;
204. inputting the positioning state quantity at the previous moment into a conversion function to obtain a first positioning state quantity at the current moment;
in this embodiment, the positioning state quantity and covariance are updated by correction:
thereby obtaining the state estimation result of the extended Kalman filter
And the corresponding covariance matrix ≥>
Wherein the content of the first and second substances,
i.e. the result of the positioning status determined by the system, is based on>
Then for the next prediction step.
205. Correcting the first positioning state quantity according to the acquired data at the current moment to obtain the positioning state quantity at the current moment;
206. calling the collected data at the previous moment and the current moment and the positioning state quantity at the previous moment;
207. calculating a second positioning state quantity based on the acquired data and the positioning state quantity at the previous moment;
208. calculating to obtain the jumping quantity of the current moment based on the acquired data of the current moment and the second positioning state quantity;
209. calculating a second-order determinant of a jump variable to obtain a jump judgment value at the current moment;
210. determining whether a sensor corresponding to the jump judgment value is positioned abnormally based on the size of the jump judgment value;
in this embodiment, a reasonable threshold is preset for the jump judgment value, and whether the sensor is determined to be abnormally positioned is determined by judging whether the jump judgment value exceeds the preset threshold.
211. Recording the sensor determined as abnormal positioning to a jump detection result; (ii) a
Specifically, the position of the previous time is
Velocity V k-1 (v x,-1 ,v y, ,v z,k-1 ) The speed at the present moment is V k (v x,k ,v y,k ,v z, ) The time interval is dt. Then, the position at the present time can be predicted, and a second positioning state quantity regarding the position is obtained:
position where acquired data is to be acquired
And a positioning status quantity position corresponding to the time>
Solving the deviation:
P jump i.e. the jump amount of the position. When P jump If |2, that is, the jump judgment amount is greater than the threshold, it indicates that the position of the estimation result between the two moments is changed without conforming to the kinematics principle, so that the system sends out the fault judgment of the sensor corresponding to the position at the moment, and determines the fault judgment as abnormal positioning.
At the last moment has the posture of
IMU measured angular velocity W k-1 (v p,1 ,v r, ,v y, ) Angular velocity at the present time is W k (v p, ,v r, ,v y,k ) The time interval is dt. Then, the attitude at the current time can be predicted, and a second positioning state quantity related to the attitude is obtained:
attitude to be acquired data acquisition
And a positioning status quantity position corresponding to the time>
Solving the deviation:
R jump i.e. the jump amount of the position. When | | | R jump If |2, that is, the jump judgment amount is greater than the threshold, it is indicated that the estimation result of the attitude changes between the two moments without conforming to the kinematics principle, so that the system sends out the fault judgment of the sensor corresponding to the attitude at the momentAnd (4) determining the fault as abnormal positioning.
Velocity at last moment is V k-1 (v x,1 ,v y,k-1 ,v z,k-1 ) Acceleration measured by IMU is a k-1 (a x,1 ,a y, ,a z, ) Acceleration at the present time is a k (a x, ,a y, ,a z, ) The time interval is dt. Then, the speed at the current time can be predicted, and a second positioning state quantity related to the speed is obtained:
speed of acquisition of acquired data
And a positioning status quantity speed corresponding to the time>
Solving the deviation:
V jump i.e. the amount of jump in speed. When | | | V jump If the jump judgment quantity is greater than the threshold, it indicates that the estimation result of the attitude changes between the two moments, and therefore the system sends out the fault judgment of the sensor with the speed corresponding to the speed, and the fault judgment is determined as abnormal positioning.
In this embodiment, after the jump detection is performed, the sensor determined as the abnormal location is recorded in the jump detection result, and is used for determining the abnormal location where the problem occurs together with the error and ambiguity diagnosis result.
212. Calculating the error between the collected data and the positioning state quantity;
213. carrying out ambiguity diagnosis on the same state aiming at the acquired data to obtain an ambiguity diagnosis result;
214. and judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result.
On the basis of the previous embodiment, the present embodiment describes the invoking of the collected data at the previous time and the current time and the positioning state quantity at the previous time in detail; calculating a second positioning state quantity based on the acquired data and the positioning state quantity at the previous moment; calculating to obtain the jumping quantity of the current moment based on the acquired data of the current moment and the second positioning state quantity; calculating a second-order determinant of the jump variable to obtain a jump judgment value at the current moment; determining whether a sensor corresponding to the jump judgment value is positioned as an abnormal based on the size of the jump judgment value; recording the sensor determined to be abnormally located to a process of a jump detection result. Compared with the traditional method, the method has the advantages that the specific method of jump detection is defined, the sensor which does not conform to the kinematics principle is positioned by adopting the jump detection method, and the subsequent overhaul processing of the sensor with problems is facilitated for a user.
Referring to fig. 3, a third embodiment of the positioning diagnosis method according to the embodiment of the present invention includes:
301. acquiring the acquired data of a plurality of sensors and fusing the acquired data of all the sensors to obtain a positioning state quantity;
302. carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result;
303. calculating the Mahalanobis distance and the absolute error of the acquired data at the current moment and the positioning state quantity at the current moment;
in the present embodiment, the calculation process of mahalanobis distance and absolute error is described by taking the collected data and the positioning state quantity of the lidar sensor as an example.
Specifically, the data collected by the laser radar at the k-th moment is as follows:
the positioning state quantity of the positioning system is as follows: />
Observation ofThe function has a function on the value of the Jacobian matrix at->
The result of here is->
And calculating the deviation between the positioning state quantity and the acquired data as follows:
the measurement noise covariance of the lidar is
The covariance matrix of the measurement errors is:
the mahalanobis distance is:
the absolute error is:
304. determining whether a sensor or a positioning system corresponding to the mahalanobis distance and the absolute error is positioned as an abnormal position based on the magnitudes of the mahalanobis distance and the absolute error;
in this embodiment, the absolute error reflects the most intuitive amount of error between the collected data of the sensor and the estimate of the positioning system. If the absolute error is too large, it indicates that there is too large deviation between the data collected by the sensor and the positioning state quantity of the positioning, and one of the two is in fault. The mahalanobis distance is a covariance matrix with introduced measurement errors, and reflects the influence of the acquired data of the sensor on the positioning result after fusion. When the mahalanobis distance of the sensor is too large, it indicates that there is a large deviation between the sensor measurement and the estimation of the positioning system, and the measurement result has a great influence on the estimation of the positioning system and is ambiguous with the measurement of other sensors.
Specifically, the sensors for calculating mahalanobis distance and absolute error at least include attitude measurement of laser radar, speed measurement of wheeled odometer, position measurement of GNSS, speed measurement of GNSS, and attitude measurement of GNSS.
305. Recording the abnormal positioning to an error;
in the embodiment, the abnormal location is determined by a sensor and a location system, wherein the Mahalanobis distance and/or the absolute error exceed a preset threshold value, and is recorded into the error.
Specifically, in this step, the abnormal location recorded in the error should include a sensor and a location system, and the specific sensor having a problem is determined by determining the abnormal location in the subsequent step 313.
306. Calling the collected data aiming at the same state and collected at the current moment;
307. calculating to obtain an absolute deviation and a direction deviation based on the first collected data and the second collected data;
specifically, the measuring sensor of the speed in the positioning system comprises two redundant modes of a wheel type odometer and a GNSS. The wheel type odometer measures the speed as
GNSS measurement of velocity is
And solving the absolute deviation and the direction deviation of the two.
Absolute deviation:
the cross product is:
and (3) carrying out scale adjustment on the two norms of the cross product by using the two norms to obtain the direction deviation:
308. determining whether a difference of the sensors corresponding to the first collected data and the second collected data falls within an allowable range based on the magnitude of the absolute deviation and the direction deviation;
in the present embodiment, when the absolute deviation is large
And direction deviation->
And when the measured value is smaller than the corresponding preset threshold value, the measurement results of the two sensors are considered to be consistent, and the state is normal. And if one of the absolute deviation or the direction deviation is larger than a set threshold value, the two sensors are considered to be ambiguous, and at least one sensor has a problem.
309. If not, taking the sensor corresponding to the first acquisition data and the second acquisition data as abnormal positioning and recording the abnormal positioning to an ambiguity diagnosis result;
310. respectively obtaining abnormal positioning in the judgment results;
in this embodiment, the determination result includes the jump detection result, the error, and the abnormal positioning recorded in the ambiguity diagnosis result. And comparing the abnormal positioning at the same or similar moments to determine the specific sensor or positioning system with problems.
311. Judging whether the abnormal positioning in the jump detection result, the error and the ambiguity diagnosis result has a consistent item or not;
in this embodiment, the jump detection result is used to determine the sensor that changes according to the principles of kinematics, the error is used to determine the sensor and/or the positioning system that has the error, the ambiguity diagnosis result is used to determine the two sensors that have ambiguity, and the sensor or the positioning system that has the problem is positioned by determining the abnormal positioning between the three results and searching for the consistent item.
312. If so, excluding the abnormal positioning only existing in the error and ambiguity diagnosis result, and keeping the abnormal positioning appearing in the jump detection result;
in this embodiment, if there is a consistent item, the sensor corresponding to the consistent item is a sensor that has a problem, so that a user can quickly locate the sensor having the problem. If no consistent item exists, removing repeated items among three results of the jump detection result, the error and the ambiguity diagnosis result, uniformly recording abnormal positioning of each item and reporting, wherein the abnormal positioning indicates that the judgment result cannot be well positioned to a specific sensor with a problem or more sensors with a problem cannot be accurately distinguished from normal sensors by a positioning diagnosis method, so that only the abnormal positioning with the repeated items is removed, and the singularity of the abnormal positioning is kept and recorded to narrow the range of the judgment result, thereby facilitating further judgment of a user.
313. If not, removing the abnormal positioning of the repeated items recorded in the jump detection result, the error and the ambiguity diagnosis result and recording the abnormal positioning.
On the basis of the previous embodiment, the present embodiment describes in detail that the collected data for the same state and collected at the current time is called, wherein the collected data at least includes first collected data and second collected data; calculating an absolute deviation and a direction deviation based on the first collected data and the second collected data; determining whether a difference of sensors corresponding to the first collected data and the second collected data falls within an allowable range based on magnitudes of the absolute deviation and the directional deviation; and if not, taking the sensors corresponding to the first collected data and the second collected data as abnormal positioning and recording the process of the ambiguity diagnosis result. Compared with the traditional method, the method has the advantages that the specific ambiguity diagnosis method is refined, when the absolute deviation and the direction deviation are simultaneously smaller than the corresponding threshold values, the measurement results of the two sensors can be considered to be consistent, and the two sensors are in a normal state. And if one of the absolute deviation or the direction deviation is larger than a set threshold value, the two sensors are considered to be ambiguous, and at least one sensor has a problem.
With reference to fig. 4, the positioning diagnosis method in the embodiment of the present invention is described above, and the positioning diagnosis device in the embodiment of the present invention is described below, where an embodiment of the positioning diagnosis device in the embodiment of the present invention includes:
the acquired data fusion module 401 is configured to acquire acquired data of a plurality of sensors and perform fusion processing on the acquired data of all the sensors to obtain a positioning state quantity;
a jump detection module 402, configured to perform jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result;
an error calculation module 403, configured to calculate an error between the acquired data and the positioning state quantity;
an ambiguity diagnosis module 404, configured to perform ambiguity diagnosis on the same state for which the acquired data is directed, to obtain an ambiguity diagnosis result;
an abnormal location determining module 405, configured to determine an abnormal location existing in the positioning system based on the jump detection result, the error, and the ambiguity diagnosis result.
In the embodiment of the invention, the positioning diagnosis device runs the positioning diagnosis method and comprises the steps of acquiring the acquired data of a plurality of sensors and fusing the acquired data of all the sensors to obtain the positioning state quantity; carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result; calculating an error between the collected data and the positioning state quantity; performing ambiguity diagnosis on the same state aiming at the acquired data to obtain an ambiguity diagnosis result; and judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result. According to the method, the positioning state quantity required by positioning at the current moment is estimated by fusing acquired data acquired by a sensor based on an extended Kalman filter, and then positioning diagnosis of the sensor and the positioning system is realized by determining the sensor which does not conform to the change of a kinematic principle, the sensor and/or the positioning system with errors and determining two sensors which have ambiguity and aim at the same state, searching a consistent item in the abnormal positioning of three results and positioning the sensor or the positioning system which has problems.
Referring to fig. 5, a second embodiment of the positioning diagnostic apparatus according to the embodiment of the present invention includes:
the acquired data fusion module 401 is configured to acquire acquired data of a plurality of sensors and perform fusion processing on the acquired data of all the sensors to obtain a positioning state quantity;
a jump detection module 402, configured to perform jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result;
an error calculation module 403, configured to calculate an error between the acquired data and the positioning state quantity;
an ambiguity diagnosis module 404, configured to perform ambiguity diagnosis on the same state for which the acquired data is directed, to obtain an ambiguity diagnosis result;
an abnormal location determining module 405, configured to determine an abnormal location existing in the positioning system based on the jump detection result, the error, and the ambiguity diagnosis result.
In this embodiment, the collected data fusion module 401 is specifically configured to:
the data acquisition unit 4011 acquires the current-time acquisition data of the plurality of sensors and the previous-time positioning state quantity; the conversion unit 4012 inputs the positioning state quantity at the previous moment into the conversion function to obtain a first positioning state quantity at the current moment; and the correcting unit 4013 corrects the first positioning state quantity according to the collected data at the current time to obtain the positioning state quantity at the current time.
In this embodiment, the collected data fusion module 401 further includes a conversion function update unit 4014, where the conversion function update unit 4014 is specifically configured to:
calculating a prediction deviation value and a Kalman gain matrix based on the positioning state quantity and the acquired data at the previous moment; updating the transformation function based on the predicted deviation value and the Kalman gain matrix.
In this embodiment, the jump detecting module 402 is specifically configured to:
calling the collected data at the previous moment and the current moment and the positioning state quantity at the previous moment; calculating a second positioning state quantity based on the acquired data and the positioning state quantity at the previous moment; calculating to obtain the jumping quantity of the current moment based on the acquired data of the current moment and the second positioning state quantity; calculating a second-order determinant of the jump variable to obtain a jump judgment value at the current moment; determining whether a sensor corresponding to the jump judgment value is positioned as an abnormal based on the size of the jump judgment value; recording the sensor determined to be the abnormal location to a jump detection result.
In this embodiment, the error calculation module 403 is specifically configured to:
calculating the Mahalanobis distance and the absolute error of the acquired data at the current moment and the positioning state quantity at the current moment; determining whether a sensor or a positioning system corresponding to the mahalanobis distance and the absolute error is positioned as an abnormal location based on the magnitudes of the mahalanobis distance and the absolute error; and recording the abnormal positioning to an error.
In this embodiment, the ambiguity diagnosis module 404 is specifically configured to:
calling the collected data aiming at the same state and collected at the current moment, wherein the collected data at least comprises first collected data and second collected data; calculating an absolute deviation and a direction deviation based on the first collected data and the second collected data; determining whether a difference of sensors corresponding to the first collected data and the second collected data falls within an allowable range based on magnitudes of the absolute deviation and the directional deviation; if not, taking the sensor corresponding to the first collected data and the second collected data as abnormal location and recording the abnormal location to an ambiguity diagnosis result.
In this embodiment, the abnormal location determining module 405 is specifically configured to:
respectively obtaining abnormal positioning in judgment results, wherein the judgment results comprise the jump detection result, the error and an ambiguity diagnosis result; judging whether consistent items exist in the jump detection result, the error and the abnormal positioning in the ambiguity diagnosis result; if so, excluding the abnormal positioning only existing in the error and the ambiguity diagnosis result, and keeping the abnormal positioning appearing in the jump detection result; and if not, removing the abnormal positioning of the repeated items recorded in the jump detection result, the error and the ambiguity diagnosis result and recording the abnormal positioning.
On the basis of the previous embodiment, the specific functions of each module and the unit composition of part of the modules are described in detail, and the specific functions of the original modules are refined through the modules, so that the operation of the positioning diagnosis device is perfected, the operation reliability is improved, the actual logic among the steps is clarified, and the practicability of the device is improved.
Fig. 4 and 5 describe the positioning diagnosis apparatus in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the positioning diagnosis device in the embodiment of the present invention is described in detail from the perspective of hardware processing.
Fig. 6 is a schematic structural diagram of a positioning diagnostic apparatus 600 according to an embodiment of the present invention, which may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 610 (e.g., one or more processors) and a memory 620, and one or more storage media 630 (e.g., one or more mass storage devices) for storing applications 633 or data 632. Memory 620 and storage medium 630 may be, among other things, transient or persistent storage. The program stored in the storage medium 630 may include one or more modules (not shown), each of which may include a series of requested operations in the positioning diagnostic apparatus 600. Still further, the processor 610 may be configured to communicate with the storage medium 630 and execute a series of requested operations in the storage medium 630 on the location diagnosis apparatus 600 to implement the steps of the location diagnosis method described above.
The location diagnostic apparatus 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input-output interfaces 660, and/or one or more operating systems 631, such as Windows Server, mac OS X, unix, linux, freeBSD, and the like. Those skilled in the art will appreciate that the configuration of the positioning diagnostic device shown in fig. 6 does not constitute a limitation of the positioning diagnostic device provided herein, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, and which may also be a volatile computer-readable storage medium, having stored therein a request, which when run on a computer, causes the computer to perform the steps of the location diagnosis method.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses, and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may substantially or partially contribute to the prior art, or all or part of the technical solution may be embodied in the form of a software product, which is stored in a storage medium and includes several requests for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A localization diagnosis method, characterized in that the localization diagnosis method comprises:
acquiring the acquired data of a plurality of sensors and fusing the acquired data of all the sensors to obtain a positioning state quantity;
carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result;
calculating an error between the collected data and the positioning state quantity;
performing ambiguity diagnosis on the same state of the acquired data to obtain an ambiguity diagnosis result;
and judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result.
2. The positioning diagnosis method according to claim 1, wherein the acquiring data of the plurality of sensors and fusing the acquired data of all the sensors to obtain the positioning state quantity comprises:
acquiring the acquisition data of a plurality of sensors at the current moment and the positioning state quantity of the sensors at the previous moment;
inputting the positioning state quantity at the previous moment into a conversion function to obtain a first positioning state quantity at the current moment;
and correcting the first positioning state quantity according to the acquired data at the current moment to obtain the positioning state quantity at the current moment.
3. The positioning diagnosis method according to claim 2, before the inputting the positioning state quantity at the previous time into the conversion function to obtain the first positioning state quantity at the current time, further comprising:
calculating a prediction deviation value and a Kalman gain matrix based on the positioning state quantity and the acquired data at the previous moment;
updating the transformation function based on the predicted deviation value and the Kalman gain matrix.
4. The positioning diagnosis method according to claim 2, wherein the detecting jump fault of the positioning state quantity based on the collected data to obtain jump detection result comprises:
calling the collected data at the previous moment and the current moment and the positioning state quantity at the previous moment;
calculating a second positioning state quantity based on the acquired data and the positioning state quantity at the previous moment;
calculating to obtain the jumping quantity of the current moment based on the acquired data of the current moment and the second positioning state quantity;
calculating a second-order determinant of the jump variable to obtain a jump judgment value at the current moment;
determining whether a sensor corresponding to the jump judgment value is positioned as an abnormal based on the size of the jump judgment value;
recording the sensor determined to be the abnormal location to a jump detection result.
5. The localization diagnostic method according to claim 2, wherein the calculation error includes a Mahalanobis distance and an absolute error,
the calculating an error between the acquired data and the positioning state quantity includes:
calculating the Mahalanobis distance and the absolute error of the acquired data at the current moment and the positioning state quantity at the current moment;
determining whether a sensor or a positioning system corresponding to the mahalanobis distance and the absolute error is positioned as an abnormal location based on the magnitudes of the mahalanobis distance and the absolute error;
and recording the abnormal positioning to an error.
6. The positioning diagnosis method according to claim 2, wherein the performing ambiguity diagnosis on the same state for which the collected data is directed to obtain an ambiguity diagnosis result comprises:
calling the collected data aiming at the same state and collected at the current moment, wherein the collected data at least comprises first collected data and second collected data;
calculating an absolute deviation and a direction deviation based on the first collected data and the second collected data;
determining whether a difference of sensors corresponding to the first collected data and the second collected data falls within an allowable range based on magnitudes of the absolute deviation and the directional deviation;
and if not, taking the sensors corresponding to the first collected data and the second collected data as abnormal positions and recording the abnormal positions to an ambiguity diagnosis result.
7. The positioning diagnosis method according to any one of claims 3-6, wherein the determining abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result comprises:
respectively obtaining abnormal positioning in judgment results, wherein the judgment results comprise the jump detection result, the error and an ambiguity diagnosis result;
judging whether consistent items exist in the jump detection result, the error and the abnormal positioning in the ambiguity diagnosis result;
if so, excluding the abnormal positioning only existing in the error and the ambiguity diagnosis result, and keeping the abnormal positioning appearing in the jump detection result;
and if not, removing the abnormal positioning of the repeated items recorded in the jump detection result, the error and the ambiguity diagnosis result and recording the abnormal positioning.
8. A positioning diagnosis device, wherein the positioning diagnosis device is applied to a positioning system, the positioning system includes a plurality of sensors, and the positioning diagnosis device includes:
the acquisition data fusion module is used for acquiring the acquisition data of the sensors and fusing the acquisition data of all the sensors to obtain a positioning state quantity;
the jump detection module is used for carrying out jump fault detection on the positioning state quantity based on the collected data to obtain a jump detection result;
the error calculation module is used for calculating the error between the acquired data and the positioning state quantity;
the ambiguity diagnosis module is used for carrying out ambiguity diagnosis on the same state aimed at by the acquired data to obtain an ambiguity diagnosis result;
and the abnormal positioning judging module is used for judging abnormal positioning existing in the positioning system based on the jump detection result, the error and the ambiguity diagnosis result.
9. A positioning diagnostic apparatus characterized in that it comprises: a memory and at least one processor, the memory having requests stored therein, the memory and the at least one processor interconnected by a line;
the at least one processor invokes the request in the memory to cause the location diagnostic device to perform the steps of the location diagnostic method of any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the individual steps of the localization diagnosis method according to any one of claims 1 to 7.
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| CN117452448A (en) * | 2023-12-25 | 2024-01-26 | 合众新能源汽车股份有限公司 | High-precision positioning jump joint fault diagnosis method and vehicle positioning control system |
| CN117452448B (en) * | 2023-12-25 | 2024-04-09 | 合众新能源汽车股份有限公司 | High-precision positioning jump joint fault diagnosis method and vehicle positioning control system |
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