Anti-shake method and device for electronic rearview mirror, electronic equipment and storage medium
Through the combination of Kalman filtering algorithm and inertial conduction signals, the jitter of the electronic rearview mirror is detected and compensated, which solves the problem of jittering of the electronic rearview mirror during vehicle driving, and improves image stability and driving safety.
Patent Information
- Application Number
- CN202510291818.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-12
- Publication Date
- 2025-06-27
AI Technical Summary
Electronic rearview mirrors are prone to shake during the vehicle's driving, resulting in unstable image, affecting the driver's observation of the road conditions behind, and poses safety hazards.
By obtaining the current measurement data and historical state estimation parameters of the electronic rearview mirror, the current measured state vector is constructed, and the current estimated state vector is determined based on the Kalman filtering algorithm. If at least one element in the current estimated state vector is greater than the preset jitter threshold, it is judged that jitter phenomenon occurs, and the jitter parameter is determined by the inertial conduction signal for jitter compensation.
It realizes jitter detection in advance before image acquisition, improves the accuracy and effectiveness of jitter detection, ensures the driver's clear observation of the road conditions behind, and enhances driving safety.
Smart Images
Figure CN120213208A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of electronic rearview mirrors, and particularly to an anti-shake method, device, electronic device and storage medium for an electronic rearview mirror. Background Art
[0002] With the continuous development of automotive technology, the limitations of traditional optical rearview mirrors have gradually emerged, especially when encountering complex road conditions during vehicle driving. Traditional optical rearview mirrors are easily affected by vehicle vibrations, resulting in jitter phenomena, which affect the driver's observation of the rear road conditions and may even cause safety hazards due to blurred vision.
[0003] With the development of electronic technology, electronic rearview mirrors have gradually emerged, but there are still deficiencies in the anti-shake performance of electronic rearview mirrors, and the problem of image instability caused by vehicle vibrations has not been completely overcome. Summary of the Invention
[0004] This application provides an anti-shake method, device, electronic device and storage medium for an electronic rearview mirror to solve the technical problem of easy jitter of the electronic rearview mirror during vehicle driving.
[0005] In some embodiments of this application, an anti-shake method for an electronic rearview mirror is provided, including: obtaining the current measurement data of the electronic rearview mirror and the historical state estimation parameters at the previous moment, and constructing a current measurement state vector according to the angular velocity data and angular acceleration data in the current measurement data, where the historical state estimation parameters include historical posterior estimation covariance and historical estimation state vector; weighting the preset process noise and the historical posterior estimation covariance according to a preset forgetting factor to obtain the current prior estimation covariance, so as to determine the current estimation state vector based on the current prior estimation covariance, the historical estimation state vector and the current measurement state vector, and the preset forgetting factor is used to increase the weight of the current measurement data; if at least one estimated element in the current estimation state vector is greater than the corresponding preset jitter threshold, then determine that the jitter detection result of the electronic rearview mirror shows a jitter phenomenon.
[0006] In some embodiments of this application, if at least one estimated element in the current estimation state vector is greater than the corresponding preset jitter threshold, then determining that the jitter detection result of the electronic rearview mirror shows a jitter phenomenon includes: if the angular velocity estimated value is greater than a preset first threshold, and / or the angular acceleration estimated value is greater than a preset second threshold, then determine that the jitter detection result of the electronic rearview mirror shows a jitter phenomenon; where the estimated element includes the angular velocity estimated value and the angular acceleration estimated value, and the preset jitter threshold includes the preset first threshold and the preset second threshold.
[0007] In some embodiments of the present application, after determining that the jitter detection result of the electronic rearview mirror shows a jitter phenomenon, the method further includes: if the covariance value in the current posterior estimation covariance is greater than a preset third threshold, determining that the credibility of the jitter detection result is credible, where the current posterior estimation covariance is obtained based on the current prior estimation covariance; and / or, if the jitter detection results of multiple consecutive measurement time steps show a jitter phenomenon, determining that the credibility of the jitter detection result is credible.
[0008] In some embodiments of the present application, determining the current estimated state vector based on the current prior estimation covariance, the historical estimated state vector, and the current measured state vector includes: determining the Kalman gain based on the current prior estimation covariance, the measurement matrix of the preset measurement equation, and the measurement noise covariance; determining the current prior state estimation according to the state transition matrix and the historical estimated state vector; and determining the current estimated state vector based on the current prior state estimation, the Kalman gain, the measurement matrix, and the current measured state vector.
[0009] In some embodiments of the present application, determining the current estimated state vector based on the current prior state estimation, the Kalman gain, and the current measured state vector includes: updating the weight of the current measured state vector according to the Kalman gain; determining the initial estimated state vector based on the measurement matrix and the current prior state estimation; and determining the current estimated state vector according to the current measured state vector with updated weight, the current prior state estimation, and the initial estimated state vector.
[0010] In some embodiments of the present application, determining the current estimated state vector based on the Kalman gain, the historical estimated state vector, and the current measured state vector includes: determining the current prior state estimation according to the state transition matrix and the historical estimated state vector; updating the weight of the current measured state vector according to the Kalman gain; determining the initial estimated state vector based on the measurement matrix of the preset measurement equation and the current prior state estimation; and determining the current estimated state vector according to the current measured state vector with updated weight, the current prior state estimation, and the initial estimated state vector.
[0011] In some embodiments of the present application, after determining that the jitter detection result of the electronic rearview mirror shows a jitter phenomenon, the method further includes: obtaining the inertial conduction signal of the electronic rearview mirror; determining the jitter parameters according to the inertial conduction signal, where the jitter parameters include the jitter amplitude, the jitter frequency, and the jitter direction; and performing jitter compensation on the electronic rearview mirror based on the jitter parameters to cancel the jitter.
[0012] In some embodiments of the present application, the present application provides an anti-shake device for an electronic rearview mirror, including: an acquisition module, configured to acquire current measurement data of the electronic rearview mirror and historical state estimation parameters at the previous moment, and construct a current measurement state vector according to the angular velocity data and angular acceleration data in the current measurement data, where the historical state estimation parameters include a historical posterior estimation covariance and a historical estimated state vector; an update module, configured to weight a preset process noise and the historical posterior estimation covariance according to a preset forgetting factor to obtain a current prior estimation covariance, and determine a current estimated state vector based on the current prior estimation covariance, the historical estimated state vector, and the current measurement state vector, where the preset forgetting factor is used to increase the weight of the current measurement data; a jitter determination module, configured to, if at least one estimated element in the current estimated state vector is greater than a corresponding preset jitter threshold, determine that the jitter detection result of the electronic rearview mirror shows a jitter phenomenon.
[0013] In some embodiments of the present application, the present application provides an electronic device, including: one or more processors; a storage device, configured to store one or more programs, which, when executed by the one or more processors, cause the electronic device to implement the anti-shake method of the electronic rearview mirror as described in any one of the above.
[0014] In some embodiments of the present application, the present application provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor of a computer, causes the computer to execute the anti-shake method of the electronic rearview mirror as described in any one of the above.
[0015] Advantages of the embodiments of the present application: The present application provides an anti-shake method, device, electronic device, and storage medium for an electronic rearview mirror. In the embodiments of the present application, a jitter index is indirectly determined through a state vector including angular velocity and angular acceleration, and it is possible to determine whether the electronic rearview mirror has a jitter phenomenon based on the current estimated state vector in combination with a preset jitter threshold, and jitter detection can be performed in advance before image acquisition; by introducing a preset forgetting factor, during the update process of the current prior estimation covariance, attention is paid to the current measurement data, improving the accuracy of jitter detection.
[0016] It should be understood that the above general description and subsequent detailed description are only exemplary and explanatory, and cannot limit the present application. Description of the Drawings
[0017] The accompanying drawings here are incorporated into and form a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application. Obviously, the accompanying drawings in the following description are only some embodiments of this application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts. In the drawings:
[0018] Figure 1 A schematic diagram showing an exemplary system architecture to which the technical solution of the embodiment of this application can be applied;
[0019] Figure 2 A schematic flowchart showing the anti-shake method of an electronic rearview mirror according to an embodiment of this application;
[0020] Figure 3 A block diagram showing the anti-shake device of an electronic rearview mirror according to an embodiment of this application;
[0021] Figure 4 A schematic diagram showing the structure of a computer system of an electronic device suitable for implementing the embodiment of this application. Detailed implementation manners
[0022] The following uses specific specific examples to illustrate the implementation manners of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.
[0023] The diagrams provided in the following embodiments only illustrate the basic concept of this application schematically. Therefore, only the components related to this application are shown in the diagrams, rather than being drawn according to the number, shape, and size of the components in actual implementation. The actual form, number, and proportion of each component during actual implementation can be arbitrarily changed, and the layout form of the components may also be more complex.
[0024] In the following description, a large number of details are explored to provide a more thorough explanation of the embodiments of this application. However, it is obvious to those skilled in the art that the embodiments of this application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of this application difficult to understand.
[0025] Please refer to Figure 1 , Figure 1The figure shows a schematic diagram of an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied. As Figure 1 shown, the system architecture may include a motion detection module 101, a main control processor 102, an image sensor 103, and a display screen 104. Among them, the motion detection module 101 includes a gyroscope for measuring the angular velocity, obtaining the current angular velocity, and transmitting it to the main control processor 102 for anti-shake control; the image sensor 103, the main control processor 102, and the display screen 104 respectively provide the functions of image perception, image processing, and image display of the electronic rearview mirror.
[0026] Exemplarily, the main control processor 102 acquires the current measurement data of the electronic rearview mirror and the historical state estimation parameters of the previous moment, and constructs a current measurement state vector according to the angular velocity data and angular acceleration data in the current measurement data. The historical state estimation parameters include the historical posterior estimation covariance and the historical estimation state vector; the preset process noise and the historical posterior estimation covariance are weighted according to a preset forgetting factor to obtain the current prior estimation covariance, so as to determine the current estimation state vector based on the current prior estimation covariance, the historical estimation state vector, and the current measurement state vector. The preset forgetting factor is used to increase the weight of the current measurement data; if at least one estimated element in the current estimation state vector is greater than the corresponding preset jitter threshold, the jitter detection result of the electronic rearview mirror is determined to have a jitter phenomenon.
[0027] In the related art, the electronic rearview mirror still has deficiencies in anti-shake performance and fails to completely overcome the problem of image instability caused by vehicle vibration.
[0028] To solve the above technical problems, the present application provides an anti-shake method, device, electronic device, and storage medium for an electronic rearview mirror. The implementation details of the technical solution of the embodiments of the present application are elaborated in detail below.
[0029] Please refer to Figure 2 , Figure 2 which shows a schematic flow chart of an anti-shake method for an electronic rearview mirror according to an embodiment of the present application. As Figure 2 shown, in an exemplary embodiment, the anti-shake method for an electronic rearview mirror includes at least steps S210 to S230, which are introduced in detail as follows:
[0030] Step S210: Acquire the current measurement data of the electronic rearview mirror and the historical state estimation parameters of the previous moment, and construct a current measurement state vector according to the angular velocity data and angular acceleration data in the current measurement data.
[0031] Among them, the historical state estimation parameters include the historical posterior estimation covariance and the historical estimation state vector.
[0032] In some embodiments of the present application, a gyroscope of a Micro-Electro-Mechanical System (MEMS) is usually selected, which has the characteristics of small size, low power consumption, and high precision.
[0033] In some embodiments of the present application, in an electronic rearview mirror, an image sensor with high resolution and high dynamic range is selected to ensure that clear and real rearview images can be captured. The types of image sensors include CMOS (Complementary Metal-Oxide-Semiconductor) type and CCD (Charge-Coupled Device) type, which can be selected according to cost, performance, and requirements. The installation position of the image sensor should ensure that the required rearview field of view can be covered, and factors such as waterproofing, dustproofing, and earthquake resistance should be considered.
[0034] In some embodiments of the present application, a high-performance microprocessor is used as the main control processor, which is responsible for receiving data from the gyroscope, processing image signals, and controlling the operation of the anti-shake system. The main control processor needs to have sufficient memory resources and storage resources to support the processing and caching of image data. Moreover, it should also have a high-speed communication interface for data transmission with other modules.
[0035] In some embodiments of the present application, a high-brightness and high-contrast LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode) display screen is selected to display the rearview image. The size and resolution of the display screen should be selected according to actual needs to ensure that the driver can clearly see the rearview image. The installation position of the display screen should be convenient for the driver to observe, and factors such as viewing angle, reflection, and occlusion should be considered. An adjustable angle installation method can be adopted to meet the needs of different drivers.
[0036] In some embodiments of the present application, the internal components of the electronic rearview mirror are protected by a sturdy, waterproof, and dustproof housing. The housing material can be selected from plastics, metals, or composite materials. The mounting bracket should have good stability and reliability and be able to firmly mount the electronic rearview mirror on the vehicle. Suction cups, clips, or screw fixation methods can be used to ensure that the electronic rearview mirror does not shake or fall off during driving.
[0037] In some embodiments of the present application, the gyroscope measures the angular velocity data of the vehicle in three axes, that is, the angular velocity measurement value is obtained, providing information on the rotational motion of the vehicle for the present application.
[0038] In some embodiments of the present application, angular acceleration data is obtained based on the change in angular velocity data over time, that is, an angular acceleration measurement value is obtained.
[0039] In some embodiments of the present application, the acquired angular velocity data is preprocessed, and the preprocessed angular velocity data is used to construct a state vector as the angular velocity data. Among them, the preprocessing includes noise removal, filtering, and calibration to improve data quality and accuracy.
[0040] In some embodiments of the present application, the actual state vector for detecting the jitter of the electronic rearview mirror is set as follows:
[0041]
[0042] Among them, Φ is the actual state vector, ω is the actual angular velocity, is the actual angular acceleration.
[0043] In some embodiments of the present application, the present application will take the k-th moment as the current moment and the (k - 1)-th moment as the previous moment as an example to illustrate the anti-shake of the electronic rearview mirror.
[0044] In some embodiments of the present application, the current measurement state vector is as follows:
[0045]
[0046] Among them, Z k is the current measurement state vector at the k-th moment, ω zk is the angular velocity measurement value at the k-th moment, is the angular acceleration measurement value at the k-th moment.
[0047] Step S220, weight the preset process noise and the historical posterior estimation covariance according to the preset forgetting factor to obtain the current prior estimation covariance, so as to determine the current estimation state vector based on the current prior estimation covariance, the historical estimation state vector, and the current measurement state vector.
[0048] Among them, the preset forgetting factor is used to increase the weight of the current measurement data.
[0049] In some embodiments of the present application, weighting the preset process noise and the historical posterior estimation covariance according to the preset forgetting factor to obtain the current prior estimation covariance includes: determining the predicted covariance propagation term based on the state transition matrix of the preset state equation and the historical posterior estimation covariance; adjusting the weight of the predicted covariance propagation term according to the preset forgetting factor; determining the current prior estimation covariance based on the weight-adjusted predicted covariance propagation term and the process noise covariance matrix of the preset process noise.
[0050] In some embodiments of the present application, the preset state equation determined based on the kinematic principle is as follows:
[0051] Φ k = FΦ k-1 + W k-1 Equation (3)
[0052] Where, Φ k is the actual state vector at time k, F is the state transition matrix, Φ k-1 is the actual state vector at time k-1, and W k-1 is the preset process noise at time k-1.
[0053] In some embodiments of the present application, the state transition matrix is as follows:
[0054]
[0055] Where, F is the state transition matrix, and Δt is the measurement sampling period of the angular velocity.
[0056] In some embodiments of the present application, the preset process noise includes Gaussian white noise with a mean of 0 and a process noise covariance matrix of Q. Where, the process noise covariance matrix is as follows:
[0057]
[0058] Where, Q is the process noise covariance matrix, q 11 is the process noise variance corresponding to the angular velocity, q 12 and q 21 are the process noise covariances between the angular velocity and the angular acceleration, and q 22 is the process noise variance corresponding to the angular acceleration.
[0059] In some embodiments of the present application, the value of the process noise covariance matrix Q is determined based on the characteristics of the preset process noise.
[0060] In some embodiments of the present application, the historical estimated state vector at the initial time can be set according to the angular velocity measurement value corresponding to the initial time or prior knowledge. For example, the historical estimated state vector at the initial time is as follows:
[0061]
[0062] Where, is the historical estimated state vector at the initial time, ω0 is the angular velocity measurement value at the initial time, is the angular acceleration measurement value at the initial time.
[0063] In some embodiments of the present application, the historical posterior estimation covariance at the initial time is as follows:
[0064]
[0065] Among them, P0 is the historical posterior estimation covariance at the initial moment, is the initial estimation variance of the angular velocity at the initial moment, and is the initial estimation covariance between the angular velocity and the angular acceleration at the initial moment, is the initial estimation variance of the angular acceleration at the initial moment.
[0066] In some embodiments of the present application, the product of the state transition matrix, the historical posterior estimation covariance, and the transpose of the state transition matrix is determined as the predicted covariance propagation term; the product of the reciprocal of the preset forgetting factor and the predicted covariance propagation term is determined as the predicted covariance propagation term after weight adjustment; the sum of the predicted covariance propagation term after weight adjustment and the process noise covariance matrix is determined as the current prior estimation covariance.
[0067] In some embodiments of the present application, the current prior estimation covariance is as follows:
[0068] P kk-1 =μ -1 FP k-1 F T +Q Equation (8)
[0069] Among them, P kk-1 is the current prior estimation covariance at time k, μ is the preset forgetting factor, F is the state transition matrix, P k-1 is the historical posterior estimation covariance at time k-1, and Q is the process noise covariance matrix.
[0070] In some embodiments of the present application, the value range of the preset forgetting factor μ is 0 < μ ≤ 1. By weighting the historical posterior estimation covariance with the reciprocal of the preset forgetting factor μ, the historical measurement data is quickly forgotten, so as to focus on the current measurement data.
[0071] In some embodiments of the present application, the current estimated state vector is determined based on the current prior estimation covariance, the historical estimated state vector, and the current measured state vector, including: determining the Kalman gain based on the current prior estimation covariance, the measurement matrix of the preset measurement equation, and the measurement noise covariance; determining the current prior state estimation according to the state transition matrix and the historical estimated state vector; determining the current estimated state vector based on the current prior state estimation, the Kalman gain, the measurement matrix, and the current measured state vector.
[0072] In some embodiments of the present application, determining the Kalman gain based on the current prior state estimate, the measurement matrix of the preset measurement equation, and the measurement noise covariance includes: determining the predicted measurement covariance matrix based on the measurement matrix and the current prior estimate covariance, and determining the total measurement covariance matrix based on the predicted measurement covariance matrix and the measurement noise covariance of the preset measurement noise; mapping the total measurement covariance matrix from the observation space back to the state space according to the measurement matrix; determining the Kalman gain based on the mapped total measurement covariance matrix and the current prior estimate covariance.
[0073] In some embodiments of the present application, the measurement equation is as follows:
[0074] Z k =HΦ k +V k Equation (9)
[0075] where, Z k is the current measurement state vector at time k, H is the measurement matrix, Φ k is the actual state vector at time k, V k is the preset measurement noise at time k.
[0076] In some embodiments of the present application, the measurement matrix H = [1 0].
[0077] In some embodiments of the present application, the preset measurement noise includes Gaussian white noise with a mean of 0 and a measurement noise covariance of R.
[0078] In some embodiments of the present application, the product of the measurement matrix, the current prior estimate covariance, and the transpose of the measurement matrix is determined as the predicted measurement covariance matrix; the sum of the predicted measurement covariance matrix and the measurement noise covariance of the preset measurement noise is determined as the total measurement covariance matrix; the product of the transpose of the measurement matrix and the inverse of the total measurement covariance matrix is determined as the mapped total measurement covariance matrix; the product of the current prior estimate covariance and the mapped total measurement covariance matrix is determined as the Kalman gain.
[0079] In some embodiments of the present application, the Kalman gain is as follows:
[0080] K k =P kk-1 H T (HP kk-1 H T +R) -1 Equation (10)
[0081] where, K k is the Kalman gain at time k, P kk-1 is the current prior estimate covariance at time k, H is the measurement matrix, and R is the measurement noise covariance.
[0082] In some embodiments of the present application, the current prior state estimate is as follows:
[0083]
[0084] Wherein, is the current prior state estimate at time k, F is the state transition matrix, is the historical estimated state vector at time k-1.
[0085] In some embodiments of the present application, determining the current estimated state vector based on the current prior estimation covariance, Kalman gain, measurement matrix, and current measurement state vector includes: updating the weight of the current measurement state vector according to the Kalman gain; determining the initial estimated state vector based on the measurement matrix and the current prior state estimate; determining the current estimated state vector according to the weight-updated current measurement state vector, the current prior state estimate, and the initial estimated state vector.
[0086] In some embodiments of the present application, the product of the Kalman gain and the current measurement state vector is determined as the weight-updated current measurement state vector; the product of the measurement matrix and the current prior state estimate is determined as the initial estimated state vector; the sum of the current prior state estimate, the weight-updated current measurement state vector, and the negative value of the initial estimated state vector is determined as the current estimated state vector.
[0087] In some embodiments of the present application, the current estimated state vector is as follows:
[0088]
[0089] Wherein, is the current estimated state vector at time k, is the current prior state estimate at time k, K k is the Kalman gain at time k, Z k is the current measurement state vector at time k, and H is the measurement matrix.
[0090] Step S230, if at least one estimated element in the current estimated state vector is greater than the corresponding preset jitter threshold, then determine the jitter detection result of the electronic rearview mirror as a jitter phenomenon.
[0091] In some embodiments of the present application, if at least one estimated element in the current estimated state vector is greater than the corresponding preset jitter threshold, the jitter detection result of the electronic rearview mirror is determined to have a jitter phenomenon, including: if the angular velocity estimated value is greater than the preset first threshold, and / or the angular acceleration estimated value is greater than the preset second threshold, the jitter detection result of the electronic rearview mirror is determined to have a jitter phenomenon; wherein, the estimated elements include the angular velocity estimated value and the angular acceleration estimated value, and the preset jitter threshold includes the preset first threshold and the preset second threshold.
[0092] In some embodiments of the present application, the preset first threshold M is preset ω and the preset second threshold
[0093]
[0094] In some embodiments of the present application, if the angular velocity estimated value angular acceleration estimated value is at least one of them, it is preliminarily determined that the electronic rearview mirror has a jitter phenomenon. Due to the introduction of the preset forgetting factor, the preset jitter threshold can be appropriately adjusted to adapt to the emphasis on the current measurement data.
[0095] In some embodiments of the present application, after determining that the jitter detection result of the electronic rearview mirror has a jitter phenomenon, the method further includes: if the covariance value in the current posterior estimation covariance is greater than the preset third threshold, the credibility of the jitter detection result is determined to be credible, and the current posterior estimation covariance is obtained based on the current prior estimation covariance and the Kalman gain; and / or, if the jitter detection results of multiple consecutive measurement time steps are that there is a jitter phenomenon, the credibility of the jitter detection result is determined to be credible.
[0096] In some embodiments of the present application, the current posterior estimation covariance is as follows:
[0097] P k =(I-K k H)P kk-1 Equation (13)
[0098] wherein, P k is the current posterior estimation covariance at time k, I is the identity matrix, K k is the Kalman gain at time k, H is the measurement matrix, and P kk-1 is the current prior estimation covariance at time k.
[0099] In some embodiments of the present application, the accuracy of the jitter detection result can be evaluated by combining the covariance value between the angular velocity and the angular acceleration in the current posterior estimation covariance. For example, if the covariance value is greater than the preset third threshold and the jitter detection result is that there is a jitter phenomenon, the jitter detection result can be considered credible.
[0100] In some embodiments of the present application, in order to reduce misjudgment, it is also possible to perform jitter analysis on the states of consecutive multiple measurement time steps. And due to the existence of a preset forgetting factor, data that has continuously exceeded the preset jitter threshold recently can better reflect the true jitter.
[0101] In some embodiments of the present application, the present application constructs a jitter detection model by defining a state vector including angular velocity and angular acceleration, combining a preset state equation and a preset measurement equation. The state change is described by a state transition matrix, the measured values are associated by a measurement matrix, and indirect filtering is performed based on the Kalman filter, so that jitter detection can be performed in advance before image acquisition; the present application introduces a preset forgetting factor to update the current prior estimate covariance in the prediction step. The jitter detection focuses on the current measurement data in the near term, improving the accuracy of jitter detection; and, whether the electronic rearview mirror has a jitter phenomenon can be judged based on the current estimated state vector, in combination with the preset jitter threshold and the current posterior estimate covariance.
[0102] In some embodiments of the present application, after determining that the jitter detection result of the electronic rearview mirror shows a jitter phenomenon, the method further includes: obtaining the inertial conduction signal of the electronic rearview mirror; determining jitter parameters according to the inertial conduction signal, where the jitter parameters include jitter amplitude, jitter frequency, and jitter direction; performing jitter compensation on the electronic rearview mirror based on the jitter parameters to cancel the jitter.
[0103] In some embodiments of the present application, the main control processor analyzes the angular velocity signal and the acceleration signal in the inertial conduction signal after fusion to obtain jitter parameters such as jitter amplitude, jitter frequency, and jitter direction.
[0104] In some embodiments of the present application, the main control processor drives the anti-jitter mechanism of the electronic rearview mirror to perform jitter compensation based on the jitter parameters. The anti-jitter mechanism includes a lens group or an image sensor. For example, the lens group will make small movements or adjust the angle within a preset range according to the jitter parameters to cancel the jitter of the electronic rearview mirror.
[0105] In some embodiments of the present application, the vibration state of the vehicle can be detected in real time through a gyroscope. The main control processor controls the micro motor to adjust the position of the image sensor according to the detected signal, which can effectively eliminate the jitter of the electronic rearview mirror caused by vehicle vibration, improve the driver's observation effect of the rear road conditions, and enhance driving safety; and the structure is simple, easy to install and maintain, and applicable to various types of vehicles; under different road conditions, the main control processor can adjust the working parameters of the micro motor according to the actual working conditions to achieve the best anti-jitter effect.
[0106] Please refer to Figure 3 , Figure 3The block diagram of the anti-shake device of an electronic rearview mirror according to an embodiment of the present application is shown. The device can be applied to Figure 1 the implementation environment shown, and is specifically configured in the main control processor 102. The device can also be applicable to other exemplary implementation environments and is specifically configured in other devices. The implementation environment applicable to the device is not limited in this embodiment.
[0107] As Figure 3 shown, the anti-shake device 300 of an electronic rearview mirror according to an embodiment of the present application includes: an acquisition module 301, an update module 302, and a jitter determination module 303.
[0108] Among them, the acquisition module 301 is used to acquire the current measurement data of the electronic rearview mirror, the historical state estimation parameters at the previous moment, and construct the current measurement state vector according to the angular velocity data and angular acceleration data in the current measurement data. The historical state estimation parameters include the historical posterior estimation covariance and the historical estimated state vector;
[0109] The update module 302 is used to weight the preset process noise and the historical posterior estimation covariance according to the preset forgetting factor to obtain the current prior estimation covariance, and determine the current estimated state vector based on the current prior estimation covariance, the historical estimated state vector, and the current measurement state vector. The preset forgetting factor is used to increase the weight of the current measurement data;
[0110] The jitter determination module 303 is used to determine that the jitter detection result of the electronic rearview mirror shows a jitter phenomenon if at least one estimated element in the current estimated state vector is greater than the corresponding preset jitter threshold.
[0111] The anti-shake device of the electronic rearview mirror provided in the above embodiment and the anti-shake method of the electronic rearview mirror provided in the above embodiment belong to the same concept. The specific manners in which each module and unit perform operations have been described in detail in the method embodiment and will not be elaborated here. In practical applications, the anti-shake device of the electronic rearview mirror provided in the above embodiment can, according to needs, allocate the above functions to different functional modules, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above. This is not limited here either.
[0112] An embodiment of the present application also provides an electronic device, including: one or more processors; a storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the electronic device realizes the anti-shake method of the electronic rearview mirror provided in each of the above embodiments.
[0113] Please refer to Figure 4 , Figure 4The figure shows a schematic structural diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application. Figure 4 The computer system 400 of the shown electronic device is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present application.
[0114] As Figure 4 shown, the computer system 400 includes a central processing unit 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory 402 or the program loaded from the storage section 408 into the random access memory 403, such as executing the methods in the above embodiments. In the random access memory 403, various programs and data required for system operation are also stored. The central processing unit 401, the read-only memory 402, and the random access memory 403 are connected to each other via a bus 404. The input / output interface 405 is also connected to the bus 404.
[0115] The following components are connected to the input / output interface 405: an input portion 406 including a keyboard, a mouse, etc.; an output portion 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage portion 408 including a hard disk, etc.; and a communication portion 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication portion 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read from it can be installed into the storage portion 408 as needed.
[0116] Particularly, according to the embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments of the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication portion 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the system of the present application are executed.
[0117] The computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.
[0118] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. Among them, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, as well as the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.
[0119] The units involved in the embodiments described in this application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the units themselves. Therefore, the technical solution according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of this application.
[0120] Another aspect of this application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor of the computer, it enables the computer to execute the anti-shake method of the electronic rearview mirror provided in each of the above embodiments. The computer-readable storage medium can be included in the electronic device described in the above embodiments, or can exist alone without being assembled into the electronic device.
[0121] In the above embodiments, unless otherwise specified, when using serial numbers such as "first" and "second" to describe a common object, it only indicates different instances of the same object, rather than indicating that the object to be described must be in a given order, whether in terms of time, space, sorting, or any other way.
[0122] The above embodiments only exemplarily illustrate the principles and effects of this application, rather than being used to limit this application. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or changes completed by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed in this application should still be covered by the claims of this application.
Claims
1. An anti-shake method for an electronic rearview mirror, characterized in that: The method comprises: Acquire current measurement data of the electronic rearview mirror and historical state estimation parameters of the previous moment, and construct a current measurement state vector according to angular velocity data and angular acceleration data in the current measurement data, wherein the historical state estimation parameters include historical posterior estimation covariance and historical estimation state vector; The preset process noise and the historical a posteriori estimated covariance are weighted according to a preset forgetting factor to obtain a current a priori estimated covariance, so as to determine a current estimated state vector based on the current a priori estimated covariance, the historical estimated state vector and the current measured state vector, wherein the preset forgetting factor is used to increase the weight of the current measured data; If at least one estimated element in the current estimated state vector is greater than a corresponding preset jitter threshold, the jitter detection result of the electronic rearview mirror is determined as the occurrence of a jitter phenomenon.
2. The anti-shake method of the electronic rearview mirror according to claim 1, characterized in that: If at least one estimated element in the current estimated state vector is greater than a corresponding preset jitter threshold, determining the jitter detection result of the electronic rearview mirror as a jitter phenomenon, including: If the angular velocity estimation value is greater than a preset first threshold value, and / or the angular acceleration estimation value is greater than a preset second threshold value, the jitter detection result of the electronic rearview mirror is determined as a jitter phenomenon; The estimation element includes the angular velocity estimation value and the angular acceleration estimation value, and the preset jitter threshold includes the preset first threshold and the preset second threshold.
3. The anti-shake method of the electronic rearview mirror according to claim 2, characterized in that: After determining that the jitter detection result of the electronic rearview mirror is that a jitter phenomenon occurs, the method further includes: If a covariance value in a current a posteriori estimated covariance is greater than a preset third threshold, determining the credibility of the jitter detection result as credible, the current a posteriori estimated covariance being obtained based on the current a priori estimated covariance; and / or, If the jitter detection results of a plurality of consecutive measurement time steps indicate that a jitter phenomenon occurs, the credibility of the jitter detection result is determined to be credible.
4. The anti-shake method of the electronic rearview mirror according to claim 1, characterized in that: The preset process noise and the historical a priori estimated covariance are weighted according to the preset forgetting factor to obtain the current a priori estimated covariance, including: Determine a prediction covariance propagation term based on a state transfer matrix of a preset state equation and the historical a posteriori estimated covariance; Adjusting the weight of the prediction covariance propagation item according to a preset forgetting factor; The current a priori estimated covariance is determined based on the weight-adjusted prediction covariance propagation term and the process noise covariance matrix of the preset process noise.
5. The anti-shake method of the electronic rearview mirror according to claim 4, characterized in that: Determining a current estimated state vector based on the current a priori estimated covariance, the historical estimated state vector, and the current measured state vector includes: Determining a Kalman gain based on the current a priori estimated covariance, a measurement matrix of a preset measurement equation, and a measurement noise covariance; Determine a current priori state estimate based on the state transfer matrix and the historical estimated state vector; A current estimated state vector is determined based on the current a priori state estimate, the Kalman gain, the measurement matrix, and the current measured state vector.
6. The anti-shake method of the electronic rearview mirror according to claim 5, characterized in that: Determining a current estimated state vector based on the current a priori state estimate, the Kalman gain, the measurement matrix, and the current measured state vector includes: Performing weight update on the current measurement state vector according to the Kalman gain; determining an initial estimated state vector based on the measurement matrix and the current a priori state estimate; A current estimated state vector is determined according to the current measured state vector after weight update, the current a priori state estimate and the initial estimated state vector.
7. The anti-shake method of the electronic rearview mirror according to any one of claims 1 to 6, characterized in that: After determining that the jitter detection result of the electronic rearview mirror is that a jitter phenomenon occurs, the method further includes: Acquiring an inertial conduction signal of the electronic rearview mirror; Determining jitter parameters according to the inertial conduction signal, wherein the jitter parameters include jitter amplitude, jitter frequency and jitter direction; The electronic rearview mirror is subjected to jitter compensation based on the jitter parameter to offset the jitter.
8. An anti-shake device for an electronic rearview mirror, characterized in that: The device comprises: An acquisition module is used to acquire current measurement data of the electronic rearview mirror and historical state estimation parameters of the previous moment, and construct a current measurement state vector according to angular velocity data and angular acceleration data in the current measurement data, wherein the historical state estimation parameters include historical posterior estimation covariance and historical estimation state vector; An updating module, configured to weight the preset process noise and the historical a posteriori estimated covariance according to a preset forgetting factor to obtain a current a priori estimated covariance, so as to determine a current estimated state vector based on the current a priori estimated covariance, the historical estimated state vector and the current measured state vector, wherein the preset forgetting factor is used to increase the weight of the current measured data; The jitter determination module is used to determine the jitter detection result of the electronic rearview mirror as the occurrence of a jitter phenomenon if at least one estimated element in the current estimated state vector is greater than a corresponding preset jitter threshold.
9. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the anti-shake method for the electronic rearview mirror as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor of a computer, the computer is caused to execute the anti-shake method for an electronic rearview mirror according to any one of claims 1 to 7.