A password unlocking method and system

Abstract

This application discloses a password unlocking method and system. The method, applied to a target door lock, includes: receiving physically modulated target sound data sent by a target key; using an adaptive filtering algorithm to model the propagation acoustic path of the target sound data to obtain current filter tap coefficients; determining whether the current filter tap coefficients are within a preset error range of the initial filter tap coefficients; if so, unlocking the target door lock. This application can improve the security of door locks.

Description

Technical Field

[0001] This invention relates to the field of password unlocking technology, and in particular, to a password unlocking method and system. Background Technology

[0002] A voiceprint lock is a door lock based on voiceprint recognition. It collects the user's voice input and extracts the voiceprint features. Then, it compares the extracted voiceprint features with the voiceprint features in a pre-established voiceprint feature database to determine whether to unlock.

[0003] However, voiceprints are easily copied and stolen, making voiceprint locks less secure. Summary of the Invention

[0004] The embodiments of this application provide a password unlocking method and system that can improve the security of door locks.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to a first aspect of the embodiments of this application, a password unlocking method is provided, applied to a target door lock, the method comprising:

[0007] Receive physically modulated target sound data sent by the target key;

[0008] An adaptive filtering algorithm is used to model the propagation acoustic path of the target sound data to obtain the current filter tap coefficients;

[0009] Determine whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient. If so, unlock the target door lock.

[0010] In some embodiments of this application, based on the foregoing scheme, determining whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient includes:

[0011] Calculate the deviation between the current filter tap coefficients and the initial filter tap coefficients of the corresponding order to obtain the tap coefficient deviation value;

[0012] If the number of tap coefficient deviation values ​​within the preset deviation range is greater than or equal to the preset number, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

[0013] In some embodiments of this application, based on the foregoing scheme, determining whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient includes:

[0014] Calculate the autocorrelation coefficient between the current filter tap coefficients and the initial filter tap coefficients to obtain the autocorrelation coefficient value;

[0015] If the autocorrelation coefficient value is greater than or equal to the preset autocorrelation coefficient value, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

[0016] In some embodiments of this application, based on the foregoing scheme, before receiving the physically modulated target sound data sent by the target key, the method further includes:

[0017] In the initial environment, receive physically modulated target sound data sent by the target key;

[0018] An adaptive filtering algorithm is used to model the propagation acoustic path of the target sound data in the initial environment, and the initial filter tap coefficients are obtained.

[0019] According to a second aspect of the embodiments of this application, a password unlocking method is provided, applied to a target key, the method comprising:

[0020] After the target door lock is inserted, in response to the target switch operation, physically modulated sound data is generated;

[0021] The physically modulated sound data is sent to the target door lock to unlock it.

[0022] In some embodiments of this application, based on the foregoing scheme, the generation of physically modulated sound data includes:

[0023] Initial white noise is sent through the target sound generator;

[0024] The initial white noise is physically modulated to generate physically modulated sound data.

[0025] In some embodiments of this application, based on the foregoing scheme, before sending the initial white noise through the target sound generator, the method further includes:

[0026] Randomly determine the frequency band range and / or randomly equalize the energy of each frequency to obtain the initial white noise.

[0027] According to a third aspect of the embodiments of this application, a password unlocking system is provided, the system comprising: a target door lock and a target key;

[0028] The target door lock includes a lock body, a microphone, and a controller. The microphone is located inside the lock body and is used to receive physically modulated target sound data sent by the target key. The controller is used to model the propagation acoustic path of the target sound data using an adaptive filtering algorithm, obtain the current filter tap coefficients, and determine whether the current filter tap coefficients are within the preset error range of the initial filter tap coefficients. If so, the lock body is unlocked.

[0029] The target key includes a key body, a target sound generator disposed within the key body, and a target switch disposed on the key body.

[0030] In some embodiments of this application, based on the foregoing scheme, the controller is further configured to:

[0031] Calculate the deviation between the current filter tap coefficients and the initial filter tap coefficients of the corresponding order to obtain the tap coefficient deviation value;

[0032] If the number of tap coefficient deviation values ​​within the preset deviation range is greater than or equal to the preset number, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

[0033] In some embodiments of this application, based on the foregoing scheme, the controller is further configured to:

[0034] Calculate the autocorrelation coefficient between the current filter tap coefficients and the initial filter tap coefficients to obtain the autocorrelation coefficient value;

[0035] If the autocorrelation coefficient value is greater than or equal to the preset autocorrelation coefficient value, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

[0036] In some embodiments of this application, based on the aforementioned scheme, in the initial environment, the microphone receives physically modulated target sound data sent by the target key; the controller uses an adaptive filtering algorithm to model the propagation acoustic path of the target sound data in the initial environment to obtain the initial filter tap coefficients.

[0037] In some embodiments of this application, based on the foregoing scheme, the key body includes a cavity, the cavity is connected to the target sound generator, the target sound generator is used to generate initial white noise, and the initial white noise is physically modulated into target sound data after passing through the cavity.

[0038] In some embodiments of this application, based on the aforementioned scheme, the cavity is provided with multiple partitions along the axial direction, the partitions are provided with multiple openings, and the spacing of the partitions is adjustable and / or the thickness is adjustable and / or the shape of the openings is adjustable and / or the position of the openings is adjustable and / or the number of openings is adjustable and / or the angle of the openings is adjustable.

[0039] The beneficial effects of this application are as follows:

[0040] When the adaptive filtering algorithm is used to model the target sound data, the model is related to the features of the target key and the target lock. This makes the current filter tap coefficients related to the features of the target key and the target lock. Target keys and locks of the same type cannot replicate the features of the current target key and the target lock, and therefore cannot obtain the current filter tap coefficients, resulting in higher security for the target lock.

[0041] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0042] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0043] Figure 1 A flowchart of a password unlocking method according to an embodiment of this application is shown;

[0044] Figure 2 A schematic diagram illustrating the principle of modeling using the LMS algorithm in an embodiment of this application is shown;

[0045] Figure 3 A first schematic diagram of the current filter tap coefficients and the initial filter tap coefficients in an embodiment of this application is shown;

[0046] Figure 4 A second schematic diagram showing the current filter tap coefficients and the initial filter tap coefficients in an embodiment of this application is shown;

[0047] Figure 5 This illustration shows a schematic diagram of determining the initial white noise by randomly determining a frequency band range in an embodiment of this application;

[0048] Figure 6 This illustration shows a schematic diagram of determining the initial white noise by randomly equalizing the energy of each frequency in an embodiment of this application.

[0049] Figure 7 A schematic diagram of the target key in an embodiment of this application is shown. Detailed Implementation

[0050] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0051] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0052] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0053] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0054] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "multiple" means two or more.

[0055] Figure 1 A flowchart of a password unlocking method according to an embodiment of this application is shown. See also: Figure 1 This application provides a password unlocking method, including at least S1 to S3, detailed as follows:

[0056] In step S1, the physically modulated target sound data sent by the target key is received;

[0057] Specifically, when receiving target sound data, the target door lock can use its own receiver, such as a microphone, or the receiver can be installed on the target door lock. When sending sound, it can use the transmitter built into the target key, or the transmitter can be installed on the target key. When performing physical modulation, it can be done through the target key's own structure or through other external structures.

[0058] In step S2, an adaptive filtering algorithm is used to model the propagation acoustic path of the target sound data to obtain the current filter tap coefficients.

[0059] Specifically, the adaptive filtering algorithm can be either the Least Mean Square Error (LMS) algorithm or the Normalized Least Mean Square Error (NLMS) algorithm. The propagation acoustic path of the target sound data will be affected by the current environment. Small changes in the environment, such as changes in the relative positions of the target key and the target door lock, the presence of obstructions, or the presence of sound-absorbing materials, will cause changes in the propagation acoustic path of the target sound data. Therefore, in the current environment, the current filter tap coefficients are unique.

[0060] In step S3, it is determined whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient. If so, the target door lock is unlocked.

[0061] Specifically, the current filter tap coefficient can be understood as the current password, and the initial filter tap coefficient can be understood as the initial password. There may be slight differences between the current environment and the initial environment, so that the current filter tap coefficient and the initial filter tap coefficient are not exactly the same. Therefore, as long as the current filter tap coefficient is within the preset error range of the initial filter tap coefficient, the password can be considered correct and the target door lock can be unlocked.

[0062] Figure 2 This diagram illustrates the principle of modeling using the LMS algorithm in an embodiment of this application. To better understand step S2, we will use the adaptive filter algorithm as the LMS algorithm, the target key's sound generator as a white noise generator, and the target door lock's sound receiver as a microphone as an example. (See [link to relevant documentation]). Figure 2 The modeling process is explained below:

[0063] H s This is a true path impulse response model from the white noise generator to the microphone, used to measure H. s White noise is generated by a white noise generator, and an FIR transverse filter is used as the modeling filter. The LMS algorithm is then used to simulate H.s The estimated value Specifically, v(n) is a white noise data sequence, which passes through the actual secondary path H. s (z), the data arriving at the microphone is d v (n), d v (n) and real-time modeling The obtained v′(n) are superimposed to obtain e v (n) Data captured by the microphone, used for LMS algorithm iteration to update The coefficient is calculated using the following formula:

[0064]

[0065] in, Let μ be the weight coefficient vector of order n, and e be the step size. v (n)=d v (n)―v′(n)=v(n)* When it converges to the ideal state, e v (n) = 0,

[0066] Optionally, the step of employing an adaptive filtering algorithm to model the propagation acoustic path of the target sound data includes:

[0067] Obtain the preset filter order;

[0068] The target sound data is decomposed by delay according to a preset filtering order.

[0069] Optionally, determining whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient includes:

[0070] Calculate the deviation between the current filter tap coefficients and the initial filter tap coefficients of the corresponding order to obtain the tap coefficient deviation value;

[0071] If the number of tap coefficient deviation values ​​within the preset deviation range is greater than or equal to the preset number, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

[0072] Specifically, if the current filter tap coefficients have order M, then the initial filter tap coefficients also have order M. The corresponding order refers to the same order. The tap coefficient deviation value is the deviation between the current filter tap coefficient of order X and the initial filter tap coefficient of order X, where X≤M, and X and M are positive integers.

[0073] For example, the current filter tap coefficients have an Nth order, a preset deviation range of -k% to k% of N, and a preset number of M. If N is 128, k is 10, and M is 120, then if the number of tap coefficients with a deviation value between -12.8 and 12.8 is greater than or equal to 120, the current filter tap coefficients are within the preset error range of the initial filter tap coefficients; otherwise, the current filter tap coefficients are not within the preset error range of the initial filter tap coefficients.

[0074] Optionally, determining whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient includes:

[0075] Calculate the autocorrelation coefficient between the current filter tap coefficients and the initial filter tap coefficients to obtain the autocorrelation coefficient value;

[0076] If the autocorrelation coefficient value is greater than or equal to the preset autocorrelation coefficient value, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

[0077] Specifically, the autocorrelation coefficient between the current filter tap coefficients and the initial filter tap coefficients can be calculated using the following formula:

[0078]

[0079] Where r(X, Y) is the autocorrelation coefficient value, Cov(X, Y) is the covariance of X and Y, Var[X] is the variance of X, Var[Y] is the variance of Y, X is the sequence of current filter coefficients, and Y is the sequence of initial filter coefficients.

[0080] Figure 3 This illustration shows a first schematic diagram of the current filter tap coefficients and the initial filter tap coefficients in an embodiment of this application. Figure 4 A second schematic diagram showing the current filter tap coefficients and the initial filter tap coefficients in an embodiment of this application is shown. For example, see [link to relevant documentation]. Figure 3 If the preset autocorrelation coefficient value is 0.99, when the autocorrelation coefficient value is 0.994, the current filter tap coefficient is within the preset error range of the initial filter tap coefficient. (See [reference]). Figure 4 When the autocorrelation coefficient is 0.856, the current filter tap coefficient is not within the preset error range of the initial filter tap coefficient.

[0081] Optionally, before receiving the physically modulated target sound data sent by the target key, the method further includes:

[0082] In the initial environment, receive physically modulated target sound data sent by the target key;

[0083] An adaptive filtering algorithm is used to model the propagation acoustic path of the target sound data in the initial environment, and the initial filter tap coefficients are obtained.

[0084] Specifically, the methods for obtaining the initial filter tap coefficients and the current filter tap coefficients are the same, the difference being that the initial environment and the current environment are different.

[0085] According to a second aspect of the embodiments of this application, a password unlocking method is provided, applied to a target key, the method comprising:

[0086] After the target door lock is inserted, in response to the target switch operation, physically modulated sound data is generated;

[0087] The physically modulated sound data is sent to the target door lock to unlock it.

[0088] Specifically, the target switch can be a button on the target key, such as the unlock button on a car key, or an operation button on a mobile app, such as the unlock button on a car infotainment app.

[0089] Optionally, generating physically modulated sound data includes:

[0090] Initial white noise is sent through the target sound generator;

[0091] The initial white noise is physically modulated to generate physically modulated sound data.

[0092] Optionally, before sending the initial white noise through the target sound generator, the method further includes:

[0093] Randomly determine the frequency band range and / or randomly equalize the energy of each frequency to obtain the initial white noise.

[0094] Figure 5 This illustration shows a schematic diagram of determining the initial white noise by randomly determining a frequency band range in an embodiment of this application. Figure 6 This illustration shows a schematic diagram of determining the initial white noise by randomly equalizing the energy of each frequency in an embodiment of this application. See [link to relevant documentation]. Figure 5 The frequency band range is determined randomly, i.e., the frequency band range is f. min to f max The initial white noise is obtained, see [link / reference]. Figure 6 Randomly equalize the energy at each frequency to obtain the initial white noise.

[0095] Specifically, by changing the frequency band range and / or the energy of each frequency, the initial white noise sent by the target sound generator is different, so that the current filter tap coefficients and the initial filter tap coefficients of different keys are also different, in order to ensure the uniqueness of the target key.

[0096] According to a third aspect of the embodiments of this application, a password unlocking system is provided, the system comprising: a target door lock and a target key;

[0097] The target door lock includes a lock body, a microphone, and a controller. The microphone is located inside the lock body and is used to receive physically modulated target sound data sent by the target key. The controller is used to model the propagation acoustic path of the target sound data using an adaptive filtering algorithm, obtain the current filter tap coefficients, and determine whether the current filter tap coefficients are within the preset error range of the initial filter tap coefficients. If so, the lock body is unlocked.

[0098] The target key includes a key body, a target sound generator disposed within the key body, and a target switch disposed on the key body.

[0099] Specifically, the controller can be a DSP chip, the target sound data can be sent to the controller through a transmission module, the target sound generator can be a speaker, and when the target door lock is a car door lock and the target key is a car key, the propagation acoustic path of the target sound data can be modeled through the secondary path identification of the active noise cancellation system.

[0100] Optionally, the lock body includes a keyhole whose shape matches that of the key body, allowing the key body to be partially inserted into the keyhole.

[0101] Optionally, the controller is further configured to:

[0102] Calculate the deviation between the current filter tap coefficients and the initial filter tap coefficients of the corresponding order to obtain the tap coefficient deviation value;

[0103] If the number of tap coefficient deviation values ​​within the preset deviation range is greater than or equal to the preset number, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

[0104] Optionally, the controller is further configured to:

[0105] Calculate the autocorrelation coefficient between the current filter tap coefficients and the initial filter tap coefficients to obtain the autocorrelation coefficient value;

[0106] If the autocorrelation coefficient value is greater than or equal to the preset autocorrelation coefficient value, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

[0107] Optionally, in the initial environment, the microphone receives physically modulated target sound data sent by the target key; the controller uses an adaptive filtering algorithm to model the propagation acoustic path of the target sound data in the initial environment to obtain the initial filter tap coefficients.

[0108] Optionally, the target sound generator is used to transmit initial white noise.

[0109] Specifically, the initial white noise can be stored in the target sound generator or in the controller. In this case, in response to the operation of the target switch, the controller sends the initial white noise to the target sound generator through the transmission module.

[0110] Optionally, the key body includes a cavity connected to the target sound generator, which generates initial white noise and is physically modulated into target sound data after passing through the cavity.

[0111] Specifically, the shape of the cavity can be set according to actual needs, such as cylindrical, prismatic, or semi-cylindrical. After the key body is inserted into the lock hole, in response to the operation of the target switch, such as pressing the target switch, the target sound generator sends initial white noise. After the initial white noise passes through the cavity, it is physically modulated into target sound data. The microphone receives the target sound data, and the controller processes the target sound data to obtain the current filter tap coefficient.

[0112] Optionally, the cavity is provided with multiple partitions along the axial direction, and the partitions are provided with multiple openings. The spacing of the partitions is adjustable and / or the thickness is adjustable and / or the shape of the openings is adjustable and / or the position of the openings is adjustable and / or the number of openings is adjustable and / or the angle of the openings is adjustable.

[0113] Figure 7 A schematic diagram of the target key structure in an embodiment of this application is shown. See also: Figure 7 The structural characteristics of the cavity will affect its acoustic transfer function characteristics, that is, affect the final generated filter tap coefficients. The same white noise will form different filter tap coefficients when passing through different cavity structures. By changing the spacing and / or thickness of the partitions and / or the shape and / or position and / or number and / or angle of the openings, the cavity structure can be changed, thereby changing the result of physical modulation.

[0114] Specifically, when adjusting the spacing between the partitions, the partitions can be slid axially. In this case, the partitions and the inner wall of the cavity are slidably connected axially, for example, through a slider-groove structure. Alternatively, other partitions between two partitions can be removed to increase the distance between them. One or more partitions can be installed between adjacent partitions to decrease the distance between them. When adjusting the partition thickness, partitions of different thicknesses can be used. When adjusting the opening shape, partitions with different opening shapes can be used, such as replacing a partition with a round hole with a partition with a square hole, or partially blocking the opening with a baffle. To adjust the shape and position of the openings, you can replace the partitions with different opening positions. To adjust the number of openings, you can replace the partitions with different numbers of openings, such as replacing a partition with 10 openings with a partition with 8 openings, or blocking some openings with a baffle. For example, if a partition has 10 openings, you can block two of them with a baffle to make it a partition with 8 openings. To adjust the opening angle, you can rotate the partition, such as rotating the partition around the axis, to make the openings distributed at different angles, or you can replace the partitions with different opening angles.

[0115] Optionally, the blocking angle of the partition is adjustable and can be rotated and adjusted according to different scales. The combination of different partition angles forms a password structure, that is, the user can define its arrangement to form a plaintext password. The physical password of the cavity structure and the digital password inside the filter (filter tap coefficients) are combined to further improve security.

[0116] In summary, when using the adaptive filtering algorithm to model the target sound data, the model is related to the characteristics of the target key, target lock, and real-time environment, such as the physical characteristics of the target sound generator and microphone, and the circuit characteristics of the controller. This makes the current filter tap coefficients related to the characteristics of the target key and target lock. On the one hand, for two sets of target keys and target locks of the same type, the frequency response parameters of the target sound generator, the sensitivity of the microphone, and the circuit delay of the controller are different. This makes it impossible for the same type of target key and target lock to replicate the characteristics of the current target key and target lock, and thus it is impossible to obtain the current filter tap coefficients. On the other hand, the characteristics of the real-time environment are different each time the lock is unlocked, meaning that each operation is unreproducible and not easily cracked. For example, playing back a recording through another device will not unlock the lock, making the target lock highly secure.

[0117] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and embodiments are within the scope and spirit of this application and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Furthermore, the functional units may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0118] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0119] The units described as separate components may or may not be physically separate. Similarly, the components of the control device may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0120] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0121] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A password unlocking method, applied to a target door lock, characterized in that, include: Receive physically modulated target sound data sent by the target key; An adaptive filtering algorithm is used to model the propagation acoustic path of the target sound data to obtain the current filter tap coefficients; Determine whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient. If so, unlock the target door lock.

2. The password unlocking method according to claim 1, characterized in that, The step of determining whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient includes: Calculate the deviation between the current filter tap coefficients and the initial filter tap coefficients of the corresponding order to obtain the tap coefficient deviation value; If the number of tap coefficient deviation values ​​within the preset deviation range is greater than or equal to the preset number, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

3. The password unlocking method according to claim 1, characterized in that, The step of determining whether the current filter tap coefficient is within the preset error range of the initial filter tap coefficient includes: Calculate the autocorrelation coefficient between the current filter tap coefficients and the initial filter tap coefficients to obtain the autocorrelation coefficient value; If the autocorrelation coefficient value is greater than or equal to the preset autocorrelation coefficient value, then the current filter tap coefficient is within the preset error range of the initial filter tap coefficient.

4. The password unlocking method according to claim 1, characterized in that, Before receiving the physically modulated target sound data sent by the target key, the method further includes: In the initial environment, receive physically modulated target sound data sent by the target key; An adaptive filtering algorithm is used to model the propagation acoustic path of the target sound data in the initial environment, and the initial filter tap coefficients are obtained.

5. A password unlocking system, characterized in that, The system includes: a target door lock and a target key; The target door lock includes a lock body, a microphone, and a controller. The microphone is located inside the lock body and is used to receive physically modulated target sound data sent by the target key. The controller is used to model the propagation acoustic path of the target sound data using an adaptive filtering algorithm, obtain the current filter tap coefficients, and determine whether the current filter tap coefficients are within the preset error range of the initial filter tap coefficients. If so, the lock body is unlocked. The target key includes a key body, a target sound generator disposed within the key body, and a target switch disposed on the key body.

6. The password unlocking system according to claim 5, characterized in that, The key body includes a cavity, which is connected to the target sound generator. The target sound generator is used to generate initial white noise, which is physically modulated into target sound data after passing through the cavity.

7. The password unlocking system according to claim 6, characterized in that, The cavity is provided with multiple partitions along the axial direction. The partitions are provided with multiple openings. The spacing of the partitions is adjustable and / or the thickness is adjustable and / or the shape of the openings is adjustable and / or the position of the openings is adjustable and / or the number of openings is adjustable and / or the angle of the openings is adjustable.

Images