Wireless ranging system and method

Abstract

The invention provides a wireless ranging system and method, and the system comprises a propagation state equalizer which is used for receiving an input signal representing the propagation time of a wireless measurement signal, carrying out the propagation state equalization processing of the input signal to eliminate an equipment error and an error caused by the change of signal characteristics, and outputting a first propagation time estimation result; the propagation time equalizer is used for receiving the first propagation time estimation result, performing propagation time equalization processing on the first propagation time estimation result to eliminate errors caused by channel environment changes, and outputting a second propagation time estimation result; and a distance estimator for generating a distance estimation value based on the second propagation time estimation result. According to the method, the device error and the error caused by the signal characteristic change are eliminated through the propagation state equalizer, and the error caused by the channel environment change is eliminated through the propagation time equalizer, so that various wireless channel environments can be better adapted, the signal characteristic change can be tracked, and the wireless ranging performance is finally improved.

Description

Technical Field

[0001] This disclosure relates to the field of wireless ranging technology, and more specifically, to a wireless ranging system and method. Background Technology

[0002] In the field of wireless ranging, distance calculation is usually based on the propagation time of the wireless measurement signal: let the signal travel at time t. i Launched from the transmitter at time t r Received by the receiver, the propagation time is t d =t r -t i The distance measurement result is d = c·t d Here, c is the speed of light 3 × 10⁻⁶. 8 meters per second.

[0003] However, in practical applications, the propagation time t d Measurements are affected by a variety of factors: inherent errors in the wireless transceiver equipment (such as electrical noise and phase noise), changes in wireless signal characteristics (such as signal attenuation and phase drift), and changes in the channel environment (such as multipath reflection, channel fading, and dynamic scene switching). These factors lead to... d The measurement error increases significantly, directly affecting the accuracy and stability of distance measurement.

[0004] Existing technologies are unable to adapt to the dynamic adjustments of equipment characteristics, signal changes, and channel environment simultaneously, and cannot effectively eliminate the aforementioned errors. Summary of the Invention

[0005] This disclosure provides at least one wireless ranging system and method to effectively eliminate various errors in wireless ranging and improve the accuracy and stability of ranging.

[0006] In a first aspect, embodiments of this disclosure provide a wireless ranging system, comprising: a propagation state equalizer, a propagation time equalizer, and a distance estimator connected in sequence;

[0007] The propagation state equalizer is used to receive an input signal characterizing the propagation time of a wireless measurement signal, perform propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, and output a first propagation time estimation result.

[0008] The propagation time equalizer is used to receive the first propagation time estimation result, perform propagation time equalization processing on the first propagation time estimation result to eliminate errors caused by changes in the channel environment, and output the second propagation time estimation result.

[0009] The distance estimator is used to generate a distance estimate based on the second propagation time estimation result.

[0010] In one possible implementation, it further includes: a propagation time reliability estimator and a propagation state reliability estimator;

[0011] The input of the propagation time reliability estimator is connected to the output of the propagation time equalizer, and the output of the propagation time reliability estimator is connected to the input of the propagation time equalizer; the input of the propagation state reliability estimator is connected to the output of the propagation state equalizer, the output of the propagation time equalizer, and the output of the distance estimator, respectively, and the output of the propagation state reliability estimator is connected to the input of the propagation state equalizer;

[0012] The propagation time reliability estimator is used to generate a first update parameter based on the second propagation time estimation result, which is used to update the equalization processing parameter of the propagation time equalizer.

[0013] The propagation state reliability estimator is used to generate a second update parameter based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value, and is used to update the equalization processing parameter of the propagation state equalizer.

[0014] In one possible implementation, the wireless measurement signal is a measurement signal compliant with the Bluetooth standard; the input signal includes at least one of the following:

[0015] The measured value of the wireless measurement signal propagation time;

[0016] The signal phase corresponding to the measured propagation time;

[0017] The complex sign corresponding to the measured value of the propagation time.

[0018] In one possible implementation, when the wireless measurement signal is a Bluetooth Low Energy (BLE) channel sounding signal, the input signal is delay time information in RTT mode and complex information corresponding to the delay time in PBR mode.

[0019] In one possible implementation, the propagation state equalizer is configured to output the first propagation time estimation result according to the following steps:

[0020] Construct vectors of input signals at multiple time points, environmental noise vectors, and signal feature compensation matrices adapted to different real-world scenarios; the real-world scenarios include at least one of static scenarios and fast-moving scenarios.

[0021] The first propagation time estimation result is generated based on the vector of the multi-time input signal, the environmental noise vector, and the signal feature compensation matrix.

[0022] In one possible implementation, the first propagation time estimation result includes: propagation time results estimated individually for each actual scenario, and a comprehensive estimation result obtained by weighting the individual estimation results.

[0023] In one possible implementation, the propagation time equalizer is configured to output the second propagation time estimation result according to the following steps:

[0024] Construct a vector of first propagation time estimation results at multiple time points and a channel compensation matrix adapted to different channel scenarios; the channel scenarios include at least one of line-of-sight scenarios and non-line-of-sight scenarios;

[0025] The second propagation time estimation result is generated based on the vector of the first propagation time estimation result at multiple time points and the channel compensation matrix.

[0026] In one possible implementation, the second propagation time estimation result includes: propagation time results estimated individually for each channel scenario, and a comprehensive estimation result obtained by weighting the individual estimation results.

[0027] In one possible implementation, the distance estimator is configured to generate the distance estimate by following the steps of:

[0028] Based on the second propagation time estimation result and the instantaneous distance calculated using the speed of light, and by weighting the instantaneous distances at multiple moments, the estimated distance value is obtained.

[0029] In one possible implementation, the propagation time reliability estimator is used to generate the first update parameter according to the following steps:

[0030] Calculate the error value based on the second propagation time estimation result;

[0031] Using an adaptive algorithm, the weighting coefficients of the propagation time equalizer are dynamically adjusted based on the error value and the individual estimation results in the second propagation time estimation result, thereby generating the updated first update parameters.

[0032] In one possible implementation, the propagation state reliability estimator is used to generate the second update parameter according to the following steps:

[0033] The error value is calculated based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value.

[0034] Using an adaptive algorithm, the weighting coefficients of the propagation state equalizer are dynamically adjusted based on the error value and the individual estimation result in the first propagation time estimation result, to generate the updated second update parameters.

[0035] Secondly, this disclosure also provides a wireless ranging method, including:

[0036] The system receives an input signal characterizing the propagation time of a wireless measurement signal through a propagation state equalizer, performs propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, and outputs a first propagation time estimation result.

[0037] The first propagation time estimation result is received by the propagation time equalizer, and the propagation time equalization process is performed on the first propagation time estimation result to eliminate the error caused by changes in the channel environment, and the second propagation time estimation result is output.

[0038] The distance estimator generates a distance estimate based on the second propagation time estimation result.

[0039] In one possible implementation, it also includes:

[0040] The propagation time reliability estimator generates a first update parameter based on the second propagation time estimation result, which is used to update the equalization processing parameter of the propagation time equalizer.

[0041] The propagation state reliability estimator generates a second update parameter based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value, which is used to update the equalization processing parameters of the propagation state equalizer.

[0042] The aforementioned wireless ranging system and method employ a propagation state equalizer that receives an input signal characterizing the propagation time of a wireless measurement signal. It performs propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, outputting a first propagation time estimation result. A propagation time equalizer receives the first propagation time estimation result, performs propagation time equalization processing on the first propagation time estimation result to eliminate errors caused by changes in the channel environment, and outputs a second propagation time estimation result. The distance estimator generates a distance estimate based on the second propagation time estimation result. This disclosure uses a propagation state equalizer to perform propagation state equalization processing to eliminate errors caused by equipment errors and changes in signal characteristics, and a propagation time equalizer to perform propagation time equalization processing to eliminate errors caused by changes in the channel environment. This allows for better adaptation to various wireless channel environments, tracking changes in signal characteristics and environmental changes, and ultimately improving wireless ranging performance.

[0043] Other advantages of this disclosure will be explained in more detail in conjunction with the following description and accompanying drawings.

[0044] It should be understood that the above description is merely an overview of the technical solution of this disclosure, so as to provide a general understanding of the technical means of this disclosure and to implement it in accordance with the contents of the specification. In order to make the above and other objects, features and advantages of this disclosure more apparent and understandable, specific embodiments of this disclosure are illustrated below. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the embodiments will be briefly described below. The accompanying drawings are incorporated in and constitute a part of this specification. These drawings illustrate embodiments conforming to this disclosure and, together with the specification, serve to illustrate the technical solutions of this disclosure. It should be understood that the drawings only illustrate certain embodiments of this disclosure and should not be considered as a limitation on the scope of protection. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. Furthermore, the same reference numerals denote the same components throughout the drawings. In the drawings:

[0046] Figure 1 A schematic diagram of the architecture of a wireless ranging system provided in an embodiment of this disclosure is shown;

[0047] Figure 2 An application flowchart of a wireless ranging system provided in an embodiment of this disclosure is shown;

[0048] Figure 3 A flowchart of a wireless ranging method provided by an embodiment of this disclosure is shown;

[0049] Figure 4 A schematic diagram of a wireless ranging device provided in an embodiment of this disclosure is shown. Detailed Implementation

[0050] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0051] In the description of embodiments disclosed herein, it should be understood that terms such as “comprising” or “having” are intended to indicate the presence of the disclosed features, figures, steps, behaviors, components, portions or combinations thereof in this specification, and do not exclude the possibility of the presence of one or more other features, figures, steps, behaviors, components, portions or combinations thereof.

[0052] Unless otherwise stated, " / " means "or". For example, A / B can mean A or B. In this article, "and / or" is merely a way of describing the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A alone, A and B at the same time, and B alone.

[0053] The terms "first," "second," etc., are used only for ease of description to distinguish identical or similar technical features and should not be construed as indicating or implying the relative importance or number of these technical features. Therefore, a feature defined by "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of embodiments of this disclosure, unless otherwise stated, the term "multiple" means two or more.

[0054] Research has found that in practical applications, the propagation time t d Measurements are affected by a variety of factors: inherent errors in the wireless transceiver equipment (such as electrical noise and phase noise), changes in wireless signal characteristics (such as signal attenuation and phase drift), and changes in the channel environment (such as multipath reflection, channel fading, and dynamic scene switching). These factors lead to... d The measurement error increases significantly, directly affecting the accuracy and stability of distance measurement.

[0055] Existing technologies are unable to adapt to the dynamic adjustments of equipment characteristics, signal changes, and channel environment simultaneously, and cannot effectively eliminate the aforementioned errors.

[0056] To at least partially address one or more of the aforementioned problems and other potential issues, this disclosure provides a wireless ranging system and method capable of adapting to various wireless channel environments, tracking changes in signal characteristics and the environment, and ultimately improving ranging performance. The aforementioned wireless ranging system and method have the following characteristics:

[0057] 1. Perform independent equilibrium and reliability estimates for the propagation state and propagation time, respectively.

[0058] 2. Perform equalization and reliability estimation on the propagation state to eliminate errors caused by equipment errors and changes in signal characteristics.

[0059] 3. Perform equalization and reliability estimation on propagation time to eliminate errors caused by changes in the channel environment.

[0060] To facilitate understanding of this embodiment, a wireless ranging system disclosed in this disclosure will first be described in detail. For example... Figure 1 The diagram illustrates a wireless ranging system provided in an embodiment of this disclosure. The system includes: a propagation state equalizer 11, a propagation time equalizer 22, and a distance estimator 33 connected sequentially; wherein:

[0061] The propagation state equalizer 11 is used to receive the input signal characterizing the propagation time of the wireless measurement signal, perform propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, and output the first propagation time estimation result.

[0062] The propagation time equalizer 22 is used to receive the first propagation time estimation result, perform propagation time equalization processing on the first propagation time estimation result to eliminate errors caused by changes in the channel environment, and output the second propagation time estimation result.

[0063] Distance estimator 33 is used to generate distance estimates based on the second propagation time estimation results.

[0064] The wireless ranging system provided in this disclosure significantly reduces propagation time measurement errors by using two-level processing of "propagation state equalization and propagation time equalization" to specifically eliminate equipment errors, signal characteristic changes, and channel environment interference.

[0065] Specifically, propagation state equalization is achieved through propagation state equalizer 11. Propagation state equalizer 11 receives an input signal characterizing the propagation time of the wireless measurement signal, performs propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, and outputs a first propagation time estimation result. Propagation time equalization is achieved through propagation time equalizer 22. Propagation time equalizer 22 receives the first propagation time estimation result, performs propagation time equalization processing on the first propagation time estimation result to eliminate errors caused by changes in the channel environment, and outputs a second propagation time estimation result. This facilitates the distance estimator 33 in generating a distance estimate based on the second propagation time estimation result. Since this distance estimate is a relevant ranging value that eliminates various error sources such as equipment errors, changes in signal characteristics, and channel environment interference, its accuracy is higher.

[0066] It should be noted that the embodiments disclosed herein are mainly applicable to any wireless communication scenario in which propagation time information is obtained through wireless measurement signals. Here, the wireless measurement signals are measurement signals that conform to the Bluetooth standard, including but not limited to Bluetooth channel sounding signals.

[0067] The input signal here can take many forms, such as a measurement of the propagation time of a wireless measurement signal; it can also be the signal phase corresponding to the measurement of the propagation time; or it can be a complex sign corresponding to the measurement of the propagation time. This disclosure does not impose specific limitations on this. In addition, when using a Bluetooth Low Energy (BLE) channel sounding signal as a wireless measurement signal, the input signal here is delay time information in Round-Trip Time (RTT) mode, and can be complex information corresponding to the delay time in Phase-Based Ranging (PBR) mode.

[0068] To further improve the stability of ranging results while ensuring higher measurement accuracy, this embodiment of the present disclosure also combines two reliability estimators (i.e., propagation time reliability estimator 44 and propagation state reliability estimator 55) to perform state / time reliability estimation. Here, the reliability estimators update parameters through real-time error feedback, enabling the system to adaptively adapt to different actual scenarios (such as stationary / moving) and different channel scenarios (such as line-of-sight scenarios and non-line-of-sight scenarios), ensuring the stability of ranging results.

[0069] like Figure 1 As shown, the input of the propagation time reliability estimator 44 is connected to the output of the propagation time equalizer 22, and the output of the propagation time reliability estimator 44 is connected to the input of the propagation time equalizer 22; the input of the propagation state reliability estimator 55 is connected to the output of the propagation state equalizer 11, the output of the propagation time equalizer 22, and the output of the distance estimator 33, respectively, and the output of the propagation state reliability estimator 55 is connected to the input of the propagation state equalizer 11; wherein:

[0070] The propagation time reliability estimator 44 is used to generate a first update parameter based on the second propagation time estimation result, which is used to update the equalization processing parameter of the propagation time equalizer 22.

[0071] The propagation state reliability estimator 55 is used to generate a second update parameter based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value, and is used to update the equalization processing parameter of the propagation state equalizer 11.

[0072] In other words, the propagation time reliability estimator 44 in this embodiment improves the system's adaptability to different channel scenarios by updating the parameters of the propagation time equalizer 22, and the propagation state reliability estimator 55 improves the system's adaptability to different actual scenarios by updating the parameters of the propagation state equalizer 11, thereby ensuring the stability of the ranging results.

[0073] To facilitate a further understanding of the wireless ranging system provided in the embodiments of this disclosure, the following will be combined with... Figure 2 A specific example will be described.

[0074] like Figure 2 As shown, the wireless ranging system provided in this embodiment consists of a propagation time equalizer 22, a propagation time reliability estimator 44, a propagation state equalizer 11, a propagation state reliability estimator 55, and a distance estimator 33.

[0075] p(t) represents the actual propagation time t of the wireless measurement signal at time t. d The measured value, the actual p(t), can be the actual propagation time t. d Time measurement t m , or t m The corresponding measurement signal phase 2πf c t m (where f) c (for measuring the wireless carrier frequency of the signal), or t m The complex symbol of the corresponding measurement signal p(t) data that conforms to the above characteristics and format are applicable to this disclosure.

[0076] Taking BLE channel sounding as an example, channel sounding has two measurement modes: time-based (RTT) mode and phase-based (PBR) mode. In RTT mode, p(t) represents the delay time information t. d In PBR mode, p(t) is the complex information phase correction term (PCT) corresponding to the delay time.

[0077] in:

[0078] w(t) is the propagation time estimate after performing propagation state equilibrium on p(t) (i.e., the first propagation time estimate).

[0079] v(t) is the propagation time estimate obtained after propagation time equalization based on w(t) (i.e., the second propagation time estimate).

[0080] y(t) is the distance estimate obtained from v(t).

[0081] After v(t) is used to estimate the propagation time reliability, the output result f(t) is used to update the propagation time equalizer 22.

[0082] After estimating the propagation state reliability using w(t), v(t), and y(t), the output result e(t) is used to update the propagation state equalizer 11.

[0083] In practical applications, the propagation time equalizer 22 is updated once every time a new v(t) is output, and the propagation state equalizer 11 is updated once every time w(t)->v(t)->y(t) is calculated, and the updates are performed continuously over a continuous period of time.

[0084] The first propagation time estimation result in this embodiment can be determined according to the following steps:

[0085] Step 1: Construct vectors of input signals at multiple time points, environmental noise vectors, and signal feature compensation matrices adapted to different real-world scenarios; real-world scenarios include at least one of static scenarios and fast-moving scenarios.

[0086] Step 2: Based on the vectors of the input signals at multiple time points, the environmental noise vector, and the signal feature compensation matrix, generate the first propagation time estimation result.

[0087] The first propagation time estimation results here include: propagation time results estimated individually for each actual scenario, and a comprehensive estimation result obtained by weighting the individual estimation results.

[0088] The second propagation time estimation result in this embodiment can be determined according to the following steps:

[0089] Step 1: Construct a vector of first propagation time estimation results at multiple time points and a channel compensation matrix adapted to different channel scenarios; the channel scenarios include at least one of line-of-sight scenarios and non-line-of-sight scenarios.

[0090] Step 2: Based on the vector and channel compensation matrix of the first propagation time estimation results at multiple time points, generate the second propagation time estimation results.

[0091] The second propagation time estimation results here include: propagation time results estimated individually for each channel scenario, and a comprehensive estimation result obtained by weighting the individual estimation results.

[0092] Based on the determined second propagation time estimate and the instantaneous distance calculated using the speed of light, and by weighting the instantaneous distances at multiple moments, a distance estimate can be obtained.

[0093] The parameter updates for the propagation time reliability estimator 44 to the propagation time equalizer 22 can be achieved through the following steps:

[0094] Step 1: Calculate the error value based on the second propagation time estimation result;

[0095] Step 2: Using an adaptive algorithm, based on the error value and the individual estimation results in the second propagation time estimation result, dynamically adjust the weighting coefficients of the propagation time equalizer 22 to generate the updated first update parameters.

[0096] The parameter updates for the propagation state reliability estimator 55 and the propagation state equalizer 11 can be achieved through the following steps:

[0097] Step 1: Calculate the error value based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value;

[0098] Step 2: Using an adaptive algorithm, based on the error value and the individual estimation results in the first propagation time estimation result, dynamically adjust the weighting coefficients of the propagation state equalizer 11 to generate the updated second update parameters.

[0099] To facilitate a further understanding of the working principle of the wireless ranging system provided in the embodiments of this disclosure, the following will be combined with... Figure 2 To elaborate further.

[0100] The specific steps are as follows:

[0101] 1) The propagation state equalizer 11 performs equipment state estimation and signal characteristic tracking estimation based on p(t), eliminates errors caused by environmental noise and signal characteristic changes, and outputs the estimation result w(t).

[0102] The equalization method here can employ mathematical modeling or neural network methods, based on the measurement results of the electrical performance of the equipment, signal characteristic analysis data, etc., to train the model and obtain a better estimation model.

[0103] The following provides a method for generating a first propagation time estimation result according to an embodiment of this disclosure:

[0104] a. Store the vector R composed of p(t) at M time points, where M can be set according to the usage scenario and testing experience.

[0105]

[0106] b. Let I be the environmental noise vector, which is obtained by statistically testing electrical noise, phase noise, and other noises.

[0107] c. Select K commonly used real-world scenarios, such as static scenarios and fast-moving scenarios, and construct a signal feature compensation matrix F for each application scenario. i , i = 0, ..., K-1.

[0108] d. Obtain the propagation time estimation results w for each individual scenario. i (t)=F i *(RI), and the weighted propagation time estimate. Composition vector:

[0109]

[0110] e. Compensation matrix F i and α i The initial value (i = 0, ..., K-1) can be set according to the use case and testing experience, α i As a second update parameter, the estimate can be updated in real time based on the estimation results of the propagation state reliability estimator 55.

[0111] 2) The propagation time equalizer 22 performs wireless channel state tracking estimation based on w(t), eliminates errors caused by multipath reflection, channel fading, etc., and outputs the estimation result v(t).

[0112] The equalization method here can employ mathematical modeling or neural network methods, based on signal measurement results in a multipath environment, to train a model and obtain a better estimation model.

[0113] The following provides a method for generating a second propagation time estimation result according to an embodiment of this disclosure:

[0114] a. Extract w from w(t) est (t).

[0115] b. Store w at N time points est (t) forms a vector X, and N can be set according to the usage scenario and testing experience.

[0116]

[0117] c. Select L channel scenarios, such as line-of-sight (LOS) scenarios and non-line-of-sight (NLOS) scenarios, and construct a channel compensation matrix H for each channel scenario. i , i = 0, ..., L-1.

[0118] d. Obtain the propagation time estimation results for each individual channel scenario. i (t)=H i *X, and the weighted propagation time estimate. Composition vector:

[0119]

[0120] e. Compensation matrix H i and β i The initial value of β (i = 0, ..., L-1) can be set according to the use case and testing experience. i As the first update parameter, the estimate can be updated in real time based on the estimation results of the propagation time reliability estimator 44.

[0121] 3) The distance estimator 33 estimates the actual distance y(t) based on v(t).

[0122] a. Extract v from v(t) est (t).

[0123] bd(t) = c·v est (t), where c is the speed of light 3×10⁻⁶. 8 meters per second

[0124] c. N d The estimated values ​​of d(t) at each time point are weighted to obtain y(t), where θ i You can adjust the settings based on your testing experience.

[0125]

[0126] 4) The propagation time reliability estimator 44 updates the propagation time equalizer 22 based on v(t). Various methods can be used here, such as Least Mean Squares (LMS).

[0127] The propagation time equalizer 22 can be updated using the following method in this embodiment:

[0128] a. Extract v from v(t) est (t), the remaining elements v i (t) forms a new vector v raw .

[0129]

[0130] b. Let v a =mean(v est (ti)), (i = 1, ..., M), where M can be set based on testing experience.

[0131] v error =v(t)-v a

[0132] cf(t) represents β at time t. i The vector formed

[0133] d. Output f(t+1) = f(t) + μ f ·v error ·v raw Update β to propagation time equalizer 22. i The coefficient, and thus the parameter update of the propagation time equalizer 22, μ f You can adjust the settings based on your testing experience.

[0134] 5) The propagation state reliability estimator 55 updates the propagation time equalizer 22 based on w(t), v(t), and y(t). Various methods can be used here, such as LMS.

[0135] The following methods can be used to update the propagation state equalizer 11 in this embodiment:

[0136] a. Extract w from w(t) est (t), the remaining elements w i (t) forms a new vector w raw :

[0137]

[0138] b. Extract v from v(t) est (t).

[0139] c. Calculate the distance estimates d respectively. v d w After weighted filtering, d is obtained a The weighting coefficients a and b can be set based on testing experience.

[0140]

[0141] d a =a·d v +b·d w

[0142] dw error =f(t)-d a

[0143] ee(t) is the value of α at time t. i The vector formed

[0144] f. Output e(t+1) = e(t) + μ e ·w error ·w raw Update α to propagation time equalizer 22. i The coefficients, and thus the parameters of the propagation state equalizer 11, μ e You can adjust the settings based on your testing experience.

[0145] It should be noted that when updating the parameters of the propagation time equalizer 22 or the propagation state equalizer 11, it can be based on data collected within a continuous time period (such as the current time point t and a series of time points between t), or it can be based on data collected only at the current time point. The specific implementation can be combined with the actual ranging needs. For example, in application scenarios with relatively fast switching, data from fewer time points (such as one time point) can be used; in application scenarios with relatively smooth switching, data from more time points (such as one time point) can be used to better balance ranging accuracy and stability.

[0146] Based on this, the wireless ranging system provided in this disclosure mainly has the following technical advantages:

[0147] 1. Improved accuracy: Through two-stage processing of "propagation state equalization and propagation time equalization", the errors of propagation time measurement are significantly reduced by specifically eliminating equipment errors, signal characteristic changes and channel environment interference.

[0148] 2. Enhanced stability: The reliability estimator updates parameters through real-time error feedback, enabling the system to adapt to different scenarios (such as stationary / moving, LOS / NLOS) and ensuring stable ranging results;

[0149] 3. Good compatibility: Supports measurement signals compliant with Bluetooth standards (such as BLE Channel sounding), adapts to multiple modes such as RTT and PBR, and has a wide range of applications.

[0150] Based on the wireless ranging system provided in the above embodiments, this disclosure also provides a wireless ranging method, see [link to relevant documentation]. Figure 3 The flowchart illustrates a wireless ranging method provided in an embodiment of this disclosure, the method comprising the following steps S101 to S103:

[0151] S101: Receive the input signal representing the propagation time of the wireless measurement signal through the propagation state equalizer, perform propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, and output the first propagation time estimation result.

[0152] S102: Receive the first propagation time estimation result through the propagation time equalizer, perform propagation time equalization processing on the first propagation time estimation result to eliminate errors caused by changes in the channel environment, and output the second propagation time estimation result;

[0153] S103: Generate a distance estimate based on the second propagation time estimation result using a distance estimator.

[0154] In one possible implementation, the above method further includes:

[0155] S104: Generate a first update parameter based on the second propagation time estimation result using the propagation time reliability estimator, which is used to update the equalization processing parameter of the propagation time equalizer;

[0156] S105: The propagation state reliability estimator generates a second update parameter based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value, which is used to update the equalization processing parameters of the propagation state equalizer.

[0157] In one possible implementation, the wireless measurement signal is a measurement signal compliant with the Bluetooth standard; the input signal includes at least one of the following:

[0158] The measured value of the propagation time of a wireless measurement signal;

[0159] The signal phase corresponding to the measured propagation time;

[0160] The complex sign corresponding to the measurement of propagation time.

[0161] In one possible implementation, when the wireless measurement signal is a Bluetooth Low Energy (BLE) channel sounding signal, the input signal is delay time information in RTT mode and complex information corresponding to the delay time in PBR mode.

[0162] In one possible implementation, the first propagation time estimate is output, including:

[0163] Construct vectors of input signals at multiple time points, environmental noise vectors, and signal feature compensation matrices adapted to different real-world scenarios; real-world scenarios include at least one of static scenarios and fast-moving scenarios.

[0164] The first propagation time estimation result is generated based on the vectors of the input signals at multiple time points, the environmental noise vector, and the signal feature compensation matrix.

[0165] In one possible implementation, the first propagation time estimation result includes: propagation time results estimated individually for each actual scenario, and a comprehensive estimation result obtained by weighting the individual estimation results.

[0166] In one possible implementation, the second propagation time estimate is output, including:

[0167] Construct a vector of first propagation time estimation results at multiple time points and a channel compensation matrix adapted to different channel scenarios; the channel scenarios include at least one of line-of-sight scenarios and non-line-of-sight scenarios;

[0168] Based on the vector and channel compensation matrix of the first propagation time estimation results at multiple time points, the second propagation time estimation results are generated.

[0169] In one possible implementation, the second propagation time estimation result includes: propagation time results estimated individually for each channel scenario, and a comprehensive estimation result obtained by weighting the individual estimation results.

[0170] In one possible implementation, generating the distance estimate includes:

[0171] Based on the second propagation time estimation result and the instantaneous distance calculated using the speed of light, and by weighting the instantaneous distances at multiple moments, a distance estimate is obtained.

[0172] In one possible implementation, generating the first update parameter includes:

[0173] The error value is calculated based on the second propagation time estimation result;

[0174] Using an adaptive algorithm, the weighting coefficients of the propagation time equalizer are dynamically adjusted based on the error value and the individual estimation results in the second propagation time estimation result, thereby generating the updated first update parameters.

[0175] In one possible implementation, generating the second update parameter includes:

[0176] The error value is calculated based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value.

[0177] Using an adaptive algorithm, the weighting coefficients of the propagation state equalizer are dynamically adjusted based on the error value and the individual estimation results in the first propagation time estimation, thereby generating the updated second parameters.

[0178] In the description of this specification, references to terms such as "some possible implementations," "some implementations," "example," "specific example," or "some examples" indicate that a specific feature, structure, material, or characteristic described in connection with that implementation or example is included in at least one implementation or example of this disclosure, and the aforementioned terms do not necessarily refer to the same implementation or example. Furthermore, the described specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more implementations or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different implementations or examples described in this specification, as well as the features of different implementations or examples.

[0179] Regarding the method flowcharts of embodiments of this disclosure, certain operations are described as different steps performed in a certain order. Such flowcharts are illustrative and not restrictive. Some steps described herein may be grouped together and performed in a single operation, or some steps may be divided into multiple sub-steps, and some steps may be performed in an order different from that shown herein. The various steps shown in the flowcharts may be implemented in any way by any circuit structure and / or tangible mechanism (e.g., software running on a computer device, hardware (e.g., logic functions implemented by a processor or chip), and / or any combination thereof).

[0180] Those skilled in the art will understand that in the methods described in the above specific embodiments, the order in which the steps are written does not imply a strict execution order, and the specific execution order of each step should be determined by its function and possible internal logic.

[0181] Based on the same inventive concept, this disclosure also provides a wireless ranging device corresponding to the wireless ranging method. Since the principle of the device in this disclosure is similar to that of the wireless ranging method described above, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0182] Reference Figure 4 The diagram shown is a schematic of a wireless ranging device provided in an embodiment of this disclosure. The device includes: a first time estimation module 201, a second time estimation module 202, and a distance estimation module 203; wherein:

[0183] The first time estimation module 201 is used to receive an input signal representing the propagation time of a wireless measurement signal through a propagation state equalizer, perform propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, and output the first propagation time estimation result.

[0184] The second time estimation module 202 is used to receive the first propagation time estimation result through the propagation time equalizer, perform propagation time equalization processing on the first propagation time estimation result to eliminate errors caused by changes in the channel environment, and output the second propagation time estimation result.

[0185] The distance estimation module 203 is used to generate a distance estimate based on the second propagation time estimation result by the distance estimator.

[0186] In one possible implementation, it also includes:

[0187] The first update module 204 is used to generate a first update parameter based on the second propagation time estimation result through the propagation time reliability estimator, which is used to update the equalization processing parameter of the propagation time equalizer.

[0188] The second update module 205 is used to generate a second update parameter based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value through the propagation state reliability estimator, and is used to update the equalization processing parameter of the propagation state equalizer.

[0189] It should be noted that the apparatus in this embodiment can implement the various processes of the aforementioned method and achieve the same effects and functions, which will not be elaborated here.

[0190] This disclosure also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the wireless ranging method described in the above-described method embodiments. The storage medium may be a volatile or non-volatile computer-readable storage medium.

[0191] This disclosure also provides a computer program product carrying program code. The program code includes instructions that can be used to execute the steps of the wireless ranging method described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0192] The aforementioned computer program product can be implemented through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied in a computer storage medium; in another optional embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0193] The various embodiments in this disclosure are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments. In particular, the description of the apparatus, device, and computer-readable storage medium embodiments is simplified because they are basically similar to the method embodiments, and the relevant parts can be referred to the description of the method embodiments.

[0194] The apparatus, device, and computer-readable storage medium provided in this disclosure correspond one-to-one with the method. Therefore, the apparatus, device, and computer-readable storage medium also have similar beneficial technical effects as their corresponding methods. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the apparatus, device, and computer-readable storage medium will not be repeated here.

[0195] Those skilled in the art will understand that embodiments of this disclosure can be implemented as methods and apparatus (devices or systems), or as computer-readable storage media. Therefore, this disclosure can be implemented entirely in hardware, entirely in software, or in a combination of software and hardware. Furthermore, this disclosure can be implemented as a computer-readable storage medium on one or more computer-readable storage media containing computer-usable program code (including, but not limited to, disk storage, read-only optical disc storage (CD-ROM), optical storage, etc.).

[0196] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices or systems), and computer-readable storage media according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to create a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or block diagrams.

[0197] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article including instruction means, wherein the instruction means implement the functions specified in one or more flowcharts and / or one or more blocks in a block diagram.

[0198] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more blocks in the block diagram.

[0199] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0200] Memory can include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0201] Computer-readable media include permanent and non-permanent, removable and non-removable media, which can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of a program, or other data. Examples of computer-readable storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory, read-only memory, electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device. Furthermore, although the operations of the methods of this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Additionally, certain steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple sub-steps.

[0202] While the spirit and principles of this disclosure have been described above with reference to several specific embodiments, it should be understood that this disclosure is not limited to the disclosed specific embodiments, and the division of aspects does not imply that features in these aspects cannot be combined. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A wireless ranging system, characterized in that, include: A propagation state equalizer, a propagation time equalizer, and a distance estimator are connected in sequence. The propagation state equalizer is used to receive an input signal characterizing the propagation time of a wireless measurement signal, perform propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, and output a first propagation time estimation result. The propagation time equalizer is used to receive the first propagation time estimation result, perform propagation time equalization processing on the first propagation time estimation result to eliminate errors caused by changes in the channel environment, and output the second propagation time estimation result. The distance estimator is used to generate a distance estimate based on the second propagation time estimation result.

2. The system according to claim 1, characterized in that, Also includes: Propagation time reliability estimator and propagation state reliability estimator; The input of the propagation time reliability estimator is connected to the output of the propagation time equalizer, and the output of the propagation time reliability estimator is connected to the input of the propagation time equalizer. The input of the propagation state reliability estimator is connected to the output of the propagation state equalizer, the output of the propagation time equalizer, and the output of the distance estimator, respectively; the output of the propagation state reliability estimator is connected to the input of the propagation state equalizer. The propagation time reliability estimator is used to generate a first update parameter based on the second propagation time estimation result, which is used to update the equalization processing parameter of the propagation time equalizer. The propagation state reliability estimator is used to generate a second update parameter based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value, and is used to update the equalization processing parameters of the propagation state equalizer.

3. The system according to claim 1 or 2, characterized in that, The wireless measurement signal is a measurement signal compliant with the Bluetooth standard; the input signal includes at least one of the following: The measured value of the wireless measurement signal propagation time; The signal phase corresponding to the measured propagation time; The complex sign corresponding to the measured value of the propagation time.

4. The system according to claim 3, characterized in that, When the wireless measurement signal is a Bluetooth Low Energy (BLE) channel sounding signal, the input signal is delay time information in RTT mode and complex information corresponding to the delay time in PBR mode.

5. The system according to claim 1 or 2, characterized in that, The propagation state equalizer is used to output the first propagation time estimation result according to the following steps: Construct vectors of input signals at multiple time points, environmental noise vectors, and signal feature compensation matrices adapted to different real-world scenarios; the real-world scenarios include at least one of static scenarios and fast-moving scenarios. The first propagation time estimation result is generated based on the vector of the multi-time input signal, the environmental noise vector, and the signal feature compensation matrix.

6. The system according to claim 5, characterized in that, The first propagation time estimation result includes: propagation time results estimated individually for each actual scenario, and a comprehensive estimation result obtained by weighting each individual estimation result.

7. The system according to claim 1 or 2, characterized in that, The propagation time equalizer is used to output the second propagation time estimation result according to the following steps: Construct a vector of first propagation time estimation results at multiple time points and a channel compensation matrix adapted to different channel scenarios; the channel scenarios include at least one of line-of-sight scenarios and non-line-of-sight scenarios; The second propagation time estimation result is generated based on the vector of the first propagation time estimation result at multiple time points and the channel compensation matrix.

8. The system according to claim 7, characterized in that, The second propagation time estimation result includes: propagation time results estimated individually for each channel scenario, and a comprehensive estimation result obtained by weighting the individual estimation results.

9. The system according to claim 1 or 2, characterized in that, The distance estimator is configured to generate the distance estimate according to the following steps: Based on the second propagation time estimation result and the instantaneous distance calculated using the speed of light, and by weighting the instantaneous distances at multiple moments, the estimated distance value is obtained.

10. The system according to claim 2, characterized in that, The propagation time reliability estimator is used to generate the first update parameter according to the following steps: Calculate the error value based on the second propagation time estimation result; Using an adaptive algorithm, the weighting coefficients of the propagation time equalizer are dynamically adjusted based on the error value and the individual estimation results in the second propagation time estimation result, thereby generating the updated first update parameters.

11. The system according to claim 2, characterized in that, The propagation state reliability estimator is used to generate the second update parameter according to the following steps: The error value is calculated based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value. Using an adaptive algorithm, the weighting coefficients of the propagation state equalizer are dynamically adjusted based on the error value and the individual estimation result in the first propagation time estimation result, to generate the updated second update parameters.

12. A wireless ranging method, characterized in that, include: The system receives an input signal characterizing the propagation time of a wireless measurement signal through a propagation state equalizer, performs propagation state equalization processing on the input signal to eliminate errors caused by equipment errors and changes in signal characteristics, and outputs a first propagation time estimation result. The first propagation time estimation result is received by the propagation time equalizer, and the propagation time equalization process is performed on the first propagation time estimation result to eliminate the error caused by changes in the channel environment, and the second propagation time estimation result is output. The distance estimator generates a distance estimate based on the second propagation time estimation result.

13. The method according to claim 12, characterized in that, Also includes: The propagation time reliability estimator generates a first update parameter based on the second propagation time estimation result, which is used to update the equalization processing parameter of the propagation time equalizer. The propagation state reliability estimator generates a second update parameter based on the first propagation time estimation result, the second propagation time estimation result, and the distance estimation value, which is used to update the equalization processing parameters of the propagation state equalizer.

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