Methods for robust detection of high-frequency signal interference

Abstract

Method (400) for detecting a signal disturbance (201) of a sensor signal (200), wherein the sensor signal (200) is a sequence of measured values ​​x k to a corresponding sequence of time points k; wherein the procedure (400) comprises: - Determining (401) a reference signal (300) by applying a Kalman filter to the sensor signal (200); wherein the reference signal (300) is a sequence of reference values ​​x̌ k includes; and - Detecting (402, 403, 404) a signal disturbance (201) of the sensor signal (200) based on the reference signal (300), wherein the method (400) further comprises: - Determining (402) a deviation ε k between a measured value x k and a corresponding reference value x̌ k ; - Determining (403) an indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) at time k, based on the determined deviation ε k ; and - Disambiguation (404) between a signal disturbance (201) or a measurement error (202) of the sensor signal (200) at time k, based on the reference signal (300), wherein the disambiguation (404) comprises: - Determining a further deviation ε k+l between a measured value x k+l and a corresponding reference value x k+l at a time k + l that is after the time k at which the indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) was determined; - Determining a further indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) at time k + l, based on the further deviation ε k+l ; and - Disambiguation (404) between a signal disturbance (201) or a measurement error (202) of the sensor signal (200) based on the deviation ε k and based on the further deviation ε k+l, where disambiguation includes (404): • Determine whether the deviation ε k has a different sign than the further deviation ε k+l ; and / or • Determine whether a time interval between time k, at which the indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) was determined, and time k + l, at which the further indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) was determined, is equal to or less than a predefined period.

Description

[0001] The invention relates to a method and a corresponding device for detecting signal disturbances in a sensor signal, in particular in a sensor signal of a vehicle sensor.

[0002] A variety of sensors are used in vehicles (e.g., in a passenger car, a truck, or a motorcycle), among other things, to collect measurement data on the vehicle's driving dynamics. For example, vehicles include one or more yaw sensors to detect a rotational movement of the vehicle about its vertical axis. The sensor signals detected by the one or more sensors can then be used to implement measures to improve the vehicle's driving dynamics. For example, a sensor signal detected by a yaw sensor can be used to provide an electronic stability program in the vehicle.

[0003] In order to be able to use the sensor signal detected by a sensor in a reliable manner for the provision of vehicle functions (such as the provision of an electronic stability program), it should be ensured that the sensor signal of a sensor reflects an actual situation (e.g. that the sensor signal of a yaw sensor reflects an actual yaw movement of the vehicle).

[0004] For example, in a method described in DE 198 18 860 A1 for detecting and locating sensor faults in motor vehicles, a measurement signal is determined from a sensor to describe the dynamic behavior of the motor vehicle, a state value associated with the measurement signal is calculated from a mathematical equivalent model, an estimation error of the state value is determined, and a residual is determined from the difference between the measurement signal and a reference value corresponding to the measurement signal and formed from the state value. For the unambiguous detection and localization of sensor faults, a characteristic parameter is formed from the multiplication of the residual and the estimation error, and an error signal is generated if the characteristic parameter exceeds a limit value.

[0005] If there is legitimate doubt about the accuracy of a sensor signal, this sensor signal should be excluded from the provision of vehicle functions. For example, vehicle functions that use the sensor signal should be deactivated or their functionality reduced for safety reasons.

[0006] On the other hand, in order to avoid unnecessary shutdown of vehicle functions, it should be ensured that short-term signal disturbances of the sensor signal (e.g. due to short-term interference or other disturbance) are quickly and reliably detected as such and thus do not lead to the shutdown of a vehicle function.

[0007] This document deals with the technical task of identifying such short-term signal disturbances of a sensor signal in a reliable and timely manner and, if necessary, distinguishing them from measurement errors of the sensor signal.

[0008] The object is achieved by the independent claims. Advantageous embodiments are described, inter alia, in the dependent claims.

[0009] According to one aspect, a method for detecting a signal disturbance in a sensor signal is described. The sensor signal comprises a sequence of measured values ​​x k at a corresponding sequence of times k. The sensor signal may have been recorded by a sensor of a vehicle (e.g., a passenger car, a truck, or a motorcycle). The sensor signal may contain measured values ​​x k a yaw sensor. Thus, the sensor signal can include a rotation angle and / or a yaw angle of the vehicle about a vertical axis of the vehicle.

[0010] The method comprises determining a reference signal by applying a Kalman filter to the sensor signal. In other words, the reference signal can be determined by Kalman filtering the sensor signal. The reference signal can be a sequence of reference values ​​x̌ k In particular, the reference signal can comprise corresponding reference values ​​for the measured values ​​of the sensor signal. In other words, the reference signal can comprise corresponding reference values ​​for the measured values ​​of the sensor signal.

[0011] The method further comprises detecting a signal disturbance in the sensor signal based on the reference signal. In particular, the reference signal can be used to reliably and promptly distinguish or disambiguate between a (short-term) signal disturbance and an (inherent) measurement error in the sensor signal. The use of a Kalman filter enables the determination of a reference signal that has little or no phase delay compared to the sensor signal. This enables reliable and prompt detection of signal disturbances by comparing the reference signal with the sensor signal.

[0012] The method comprises in particular determining a deviation ε k between a measured value x k and a corresponding reference value x̌ k at time k. Deviations can be determined for the sequence of time points. Based on the determined deviation ε kan indication of a signal disturbance or a measurement error of the sensor signal is determined. In particular, an indication can be determined that at time k either a signal disturbance or a measurement error of the sensor signal is present. To determine such an indication, it can be determined that an amount of the determined deviation ε k equal to or greater than a threshold.

[0013] As already explained above, the use of a Kalman filter enables the reduction of phase lag between the sensor signal and the reference signal. This, in turn, allows the determination of indices based on the measured deviations ε k between measured values ​​x k and corresponding reference values ​​x̌ k .

[0014] The threshold for determining an indicator can depend on the energy of a noise component of the sensor signal. The noise component of the sensor signal can be determined, for example, by high-pass filtering the sensor signal. As the energy of the noise component of the sensor signal increases, the threshold can increase. By taking the energy of the noise component into account when determining an indicator of signal interference or a measurement error in the sensor signal, the detection of signal interference can be made more robust.

[0015] The method further comprises disambiguating between a signal disturbance and a measurement error of the sensor signal at time k based on the reference signal. In particular, based on the determined deviations ε k between measured values ​​x k and corresponding reference values ​​x̌ k determine whether the detected indication at time k is due to a signal disturbance or a measurement error.

[0016] Disambiguation involves determining a further deviation ε k+l between a measured value x k+l and a corresponding reference value x k+l at a time k + l which is after the time k at which the indication of a signal disturbance or a measurement error of the sensor signal was determined. In other words, deviations ε k+l at times after time k are determined and analyzed. In particular, based on the further deviation ε k+l determines that at time k + l there is another indication of a signal disturbance or a measurement error of the sensor signal. For this purpose, the amount of the deviation ε k+l be compared with the above-mentioned threshold value (which may depend on the energy of the noise component of the sensor signal).

[0017] A distinction is then made between a signal disturbance or a measurement error of the sensor signal based on the deviation ε kand based on the further deviation ε k+l disambiguated or differentiated. In particular, it can be determined whether the deviation ε k has a different sign than the further deviation ε k+l A different sign typically indicates the presence of a signal disturbance. Alternatively or additionally, it can be determined whether a time interval between time k, at which the indication of a signal disturbance or of a measurement error in the sensor signal was determined, and time k + l, at which the further indication of a signal disturbance or of a measurement error in the sensor signal was determined, is equal to or less than a predefined period. The presence of two indications within the predefined period (e.g., 50 ms or less) is an indication of the presence of a signal disturbance (especially if the deviations have a different sign).

[0018] This allows for an efficient and reliable determination of whether the sensor signal contains signal interference or a measurement error based on the reference signal and the sensor signal. This can increase the robustness and safety of vehicle functions that rely on the sensor signal.

[0019] The Kalman filter can describe a state of the vehicle by a state vector X. The state vector X at time k can be the sensor signal at time k (i.e. the measured value x k), as well as one or more derivatives of the sensor signal at time k. A state transition of the vehicle between states at different times can be described by a third-order or higher-order polynomial. The use of such a state model makes it possible to determine the feedback or Kalman gains in the Kalman filter in advance. This, in turn, enables resource-efficient calculation of the reference signal during vehicle operation.

[0020] According to a further aspect, a control unit for a vehicle is described. The vehicle comprises a sensor (e.g., a yaw sensor) for detecting a sensor signal. The sensor signal comprises a sequence of measured values ​​x kat a corresponding sequence of times k. The control unit is configured to carry out a method according to the above-described aspect of the invention and thereby detect a signal disturbance in the sensor signal. The control unit is thus configured, in particular, to determine a reference signal by applying a Kalman filter to the sensor signal. The reference signal comprises a sequence of reference values ​​x̌ corresponding to the sensor signal. k The control unit is configured to detect a signal disturbance of the sensor signal based on the reference signal.

[0021] The control unit is further configured to use the reference signal to disambiguate a signal disturbance in the sensor signal from a measurement error in the sensor signal (using the method described in this document). Furthermore, the control unit can be configured to reduce the functionality of a vehicle function that uses the sensor signal if a measurement error in the sensor signal is detected.

[0022] Alternatively or additionally, the control unit can be configured to ensure that the functionality of the vehicle function that uses the sensor signal is maintained if a signal disturbance of the sensor signal is detected.

[0023] Thus, the control unit can be configured to increase the robustness and safety of vehicle functions (e.g. of an electronic stability program) by reliably and promptly disambiguating signal interference and measurement errors.

[0024] According to a further aspect, a vehicle (e.g. a passenger car, a truck or a motorcycle) is described which comprises a control unit described in this document.

[0025] According to another aspect, a software (SW) program is described. The SW program can be configured to be executed on a processor (e.g., on a vehicle control unit) and thereby to carry out the method described in this document.

[0026] According to a further aspect, a storage medium is described. The storage medium can comprise a software program configured to be executed on a processor and thereby to carry out the method described in this document.

[0027] It should be noted that the methods, devices and systems described in this document may be used alone or in combination with other

Claims

[1] Method (400) for detecting a signal disturbance (201) of a sensor signal (200), wherein the sensor signal (200) comprises a sequence of measured values ​​x k at a corresponding sequence of times k; wherein the method (400) comprises: - determining (401) a reference signal (300) by applying a Kalman filter to the sensor signal (200); wherein the reference signal (300) comprises a sequence of reference values ​​x̌ k includes; and - detecting (402, 403, 404) a signal disturbance (201) of the sensor signal (200) on the basis of the reference signal (300), the method (400) further comprising: - Determine (402) a deviation ε k between a measured value x k and a corresponding reference value x̌ k ; - Determining (403) an indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) at time k, on the basis of the determined deviation ε k ; and - Disambiguating (404) between a signal disturbance (201) or a measurement error (202) of the sensor signal (200) at time k, based on the reference signal (300), wherein the disambiguating (404) comprises: - Determine a further deviation ε k+l between a measured value x k+l and a corresponding reference value x k+l at a time k + l which is after the time k at which the indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) was determined; - Determining a further indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) at time k + l, based on the further deviation ε k+l ; and - Disambiguating (404) between a signal disturbance (201) or a measurement error (202) of the sensor signal (200) on the basis of the deviation ε k and based on the further deviation ε k+l, where disambiguation (404) includes: • Determine whether the deviation ε k has a different sign than the further deviation ε k+l ; and / or • Determining whether a time interval between the time k at which the indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) was determined and the time k + l at which the further indication of a signal disturbance (201) or of a measurement error (202) of the sensor signal (200) was determined is equal to or less than a predefined period of time. [2] Method (400) according to any preceding claim, wherein determining (403) an indication comprises determining that an amount of the determined deviation ε k equal to or greater than a threshold. [3] Method (400) according to claim 2, wherein the threshold value depends on an energy of a noise component of the sensor signal (200). [4] Method (400) according to any preceding claim, wherein - the sensor signal (200) was detected by a sensor (102) of a vehicle (100); - the Kalman filter describes a state of the vehicle (100) by a state vector X; - the state vector X at time k comprises the sensor signal (200) at time k, as well as one or more derivatives of the sensor signal (200) at time k; and - a state transition of the vehicle (100) between states at different times is described by a third or higher order polynomial. [5] Method (400) according to any preceding claim, wherein the sensor signal (200) contains measured values ​​x k a yaw sensor (102). [6] Control unit (101) for a vehicle (100), wherein the vehicle (100) comprises a sensor (102) for detecting a sensor signal (200), wherein the sensor signal (200) comprises a sequence of measured values ​​x kat a corresponding sequence of times k; wherein the control unit (101) is configured to carry out a method (400) according to a preceding claim and thereby detect a signal disturbance (201) of the sensor signal (200). [7] Control unit (101) according to claim 6, wherein the control unit (101) is arranged - to cause a functional scope of a vehicle function that uses the sensor signal (200) to be reduced if a measurement error (202) of the sensor signal (200) is detected as a result of the disambiguation (404); and / or - to ensure that the functionality of the vehicle function that uses the sensor signal (200) is maintained if a signal disturbance (201) of the sensor signal (200) is detected as a result of the disambiguation (404). [8] Vehicle (100), wherein the vehicle (100) comprises a control unit (101) according to claim 6 or 7. [9] A software program, the software program being arranged to be executed on a processor and thereby to carry out a method (400) according to any one of claims 1 to 5. [10] A storage medium, the storage medium comprising a software program according to claim 9.

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