Method and apparatus for time-of-flight estimation

Abstract

A method for providing an estimate of the time of flight between an ultrasound signal and an ultrasound echo signal, the ultrasound signal being transmitted by a device and being returned by a target object struck by the ultrasound signal and being received at the device. The method comprises: acquiring the ultrasound echo signal to thereby obtain an electrical echo signal; determining a noise power of the electrical echo signal; determining an envelope signal indicative of an envelope of the electrical echo signal; determining a portion of the envelope signal based on at least one operating parameter, the at least one operating parameter being determined according to particle swarm optimization; processing the portion of the envelope signal and the noise power of the electrical echo signal according to an unscented Kalman filter to obtain an estimate of the envelope signal, wherein the estimate of the envelope signal is a regenerated version of the envelope signal regenerated from the portion of the envelope signal, the processing being based on at least one unscented Kalman filter parameter determined according to particle swarm optimization; and providing an estimate of the time of flight based on the estimate of the envelope signal.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of Italian Patent Application No. 102020000024874, filed on October 21, 2020, which is incorporated herein by reference. Technical Field

[0003] The present invention relates to a device for ultrasonic time-of-flight (TOF) estimation (hereinafter referred to as TOF device) and a corresponding method implemented by the TOF device. Background Art

[0004] According to the ultrasonic TOF estimation principle, an ultrasonic signal (hereinafter referred to as an ultrasonic source signal) is generated by a TOF device and transmitted toward a target body, a corresponding ultrasonic signal (hereinafter referred to as an ultrasonic echo signal) originating from the target body by reflection of the ultrasonic source signal hitting the target body is received at the TOF device, and the TOF estimation is determined as the time elapsed from the transmission of the ultrasonic source signal to the reception of the ultrasonic echo signal.

[0005] In typical applications, eg, in applications for obstacle detection, the TOF device may be configured to determine a distance estimate indicating a distance between the TOF device and a target object, eg, based on the TOF estimation.

[0006] The output of the TOF device may be a distance estimate, and / or the distance estimate may be part of additional information based on the distance estimate, such as displacement information, level information, material information, structural information, vibration information, and medical diagnostic information.

[0007] According to known implementations, TOF estimation is based on a Kalman filter, which is an algorithm that generates, through a recursive process, the best estimate of a desired quantity given a set of measured quantities.

[0008] Extended Kalman filters are also known, which are suitable for nonlinear systems. Basically, extended Kalman filters provide linearization of nonlinear systems by Jacobian calculations.

[0009] Unscented Kalman filters are also known, which are also suitable for nonlinear systems. Basically, an unscented Kalman filter provides a linearization of the probability distribution of the error.

[0010] Currently, TOF estimation based on the Unscented Kalman Filter is preferred. Summary of the Invention

[0011] Applicants have appreciated that TOF estimation based on an unscented Kalman filter has some drawbacks.

[0012] For example, Applicants have appreciated that the performance of an unscented Kalman filter is closely related to the effective calibration of a number of parameters, including parameters associated with the acquisition of ultrasound echo signals and parameters of the unscented Kalman filter.

[0013] Since there are many parameters that need to be calibrated and the calibration of these parameters is almost always done manually based on the designer's experience, the performance of the unscented Kalman filter may often be lower than expected.

[0014] Furthermore, the applicant also understands that TOF estimation may also be affected by external conditions (such as environmental conditions) during the life of the TOF device. For example, changes in air temperature, humidity, air pressure, air turbulence, and external noise may seriously affect ultrasonic signal acquisition. Therefore, parameter calibration may be insufficient due to changes in external conditions.

[0015] Last but not least, the Applicant has appreciated that the high computational complexity of current TOF estimation methods does not allow for efficient implementation in available microcontrollers.

[0016] The Applicant has faced the above-mentioned problem and has designed a method for TOF estimation and a corresponding TOF device to allow easy and dynamic adjustment (i.e., adjustment or updating or improvement or calibration) of parameters associated with the processing of acquired ultrasound echo signals and parameters of the unscented Kalman filter.

[0017] For example, one aspect of the invention relates to a method for providing an estimate of the time of flight between an ultrasonic signal emitted by a device and an ultrasonic echo signal returned by a target object struck by the ultrasonic signal and received at the device. The method may include acquiring the ultrasonic echo signal to obtain an electrical echo signal. The method may include determining a noise power of the electrical echo signal. The method may include determining an envelope signal indicative of an envelope of the electrical echo signal. The method may include determining a portion of the envelope signal based on at least one operating parameter, the at least one operating parameter being determined according to particle swarm optimization. The method may include processing the portion of the envelope signal and the noise power of the electrical echo signal according to an unscented Kalman filter to obtain an estimate of the envelope signal; the estimate of the envelope signal may be a regenerated version of the envelope signal regenerated from the portion of the envelope signal; the processing may be based, for example, on at least one unscented Kalman filter parameter (UKF) determined according to particle swarm optimization. k ). The method may comprise providing an estimate of the time of flight based on the estimate of the envelope signal.

[0018] According to one embodiment, which is additionally or alternatively characterized by one or more features of any one of the preceding embodiments, the method includes determining an estimation error. The particle swarm optimization may be based on the estimation error.

[0019] According to an embodiment, which is characterized in addition to or instead of one or more features of any one of the preceding embodiments, determining the estimation error includes determining a difference between the estimate of the envelope signal and the envelope signal.

[0020] According to one embodiment, in addition to or in lieu of one or more features of any of the preceding embodiments, the method includes determining a distance estimate indicating a distance between the target object and the device based on the estimate of the time of flight. Determining an estimation error may include determining a difference between the distance estimate and the distance.

[0021] According to an embodiment, which is characterized in addition to or instead of one or more features of any one of the preceding embodiments, determining the envelope signal comprises performing a Hilbert transform on the electrical echo signal.

[0022] According to an embodiment, in addition to or in lieu of one or more features of any one of the preceding embodiments, the portion of the envelope signal is centered around a maximum value of the envelope signal.

[0023] According to an embodiment, which is characterized in addition to or instead of one or more features of any one of the preceding embodiments, the operation of processing the envelope signal includes providing a regenerated envelope signal.

[0024] According to one embodiment, which is a supplement or replacement of one or more features of any one of the preceding embodiments, the at least one operating parameter includes at least one of the following:

[0025] an operating parameter indicating a maximum length in time of the portion of the envelope signal, and

[0026] An operating parameter is indicative of an optimized length in time of the portion of the envelope signal, the optimized length being less than the maximum length.

[0027] According to one embodiment, which is characterized in addition to or instead of one or more features of any one of the preceding embodiments, the at least one unscented Kalman filter parameter includes at least one of the following:

[0028] Evaluate parameters to provide a rough estimate of flight time;

[0029] Control parameters for controlling the spread of sigma points around the mean state value; and

[0030] The correction parameter provides correction for the noise power of the electrical echo signal.

[0031] Another aspect of the present invention relates to an apparatus for providing an estimate of the time of flight between an ultrasonic signal emitted by the apparatus and an ultrasonic echo signal returned by a target object struck by the ultrasonic signal and received at the apparatus. The apparatus may include a conditioning and conversion system for acquiring the ultrasonic echo signal to obtain an electrical echo signal. The apparatus may include means for determining a noise power of the electrical echo signal. The apparatus may include means for determining an envelope signal indicative of an envelope of the electrical echo signal. The apparatus may include means for determining a portion of the envelope signal based on at least one operating parameter; the at least one operating parameter may be determined according to particle swarm optimization. The apparatus may include means for processing the portion of the envelope signal and the noise power of the electrical echo signal according to an unscented Kalman filter to obtain an estimate of the envelope signal; the estimate of the envelope signal may be a regenerated version of the envelope signal regenerated from the portion of the envelope signal; the processing may be based on at least one unscented Kalman filter parameter determined according to particle swarm optimization. The apparatus may include means for providing an estimate of the time of flight based on the estimate of the envelope signal.

[0032] Another aspect of the invention relates to an electronic system comprising such a device (or a plurality of such devices). BRIEF DESCRIPTION OF THE DRAWINGS

[0033] These and other features and advantages of the present disclosure will become apparent from the following description of some exemplary and non-limiting embodiments thereof; for a better understanding, the following description should be read with reference to the accompanying drawings, in which:

[0034] Figure 1 Schematically illustrates a device for ultrasound flight time estimation according to an embodiment of the present disclosure;

[0035] Figure 2A and 2B An activity diagram illustrating a method according to a respective embodiment of the present disclosure;

[0036] Figure 3 The embodiment according to the present disclosure includes Figure 1 A simplified block diagram of the electronic system of the device; and

[0037] Figure 4 and 5 An activity diagram of a corresponding method according to a corresponding embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0038] With reference to the accompanying drawings, Figure 1The TOF device 100 is configured to implement a method for providing TOF estimation (hereinafter referred to as TOF method) according to an embodiment of the present disclosure.

[0039] Hereinafter, when one or more features of the TOF device and TOF method are introduced using the wording "according to one embodiment", they will be interpreted as supplementary features or alternative features to any previously introduced features, unless otherwise specified and / or unless there is an obvious incompatibility between the feature combinations.

[0040] In the following, only components of the TOF device 100 (and TOF method steps performed thereby) that are considered relevant to understanding the present disclosure will be shown and discussed, and other known components of the TOF device 100 (and TOF method steps performed thereby) will be intentionally omitted for the sake of brevity.

[0041] According to the ultrasonic flight time estimation principle, an ultrasonic signal (hereinafter referred to as an ultrasonic source signal) USS is generated by the TOF device 100 and transmitted to a target body T (the target body is outside the TOF device 100, that is, not a part of the TOF device 100), and a corresponding ultrasonic signal (hereinafter referred to as an ultrasonic echo signal) UES originating from the target body T by the reflection of the ultrasonic source signal USS hitting the target body T is received at the TOF device 100, and the TOF estimation is determined (by the TOF device 100) as the time elapsed from the transmission of the ultrasonic source signal USS to the reception of the ultrasonic echo signal UES.

[0042] According to one embodiment, the TOF device 100 is configured to determine a distance D between the TOF device 100 and the target body T, for example based on a TOF estimation. ACT The distance estimate D EST .

[0043] According to one embodiment, the TOF device 100 may be configured to further estimate the distance D based on the TOF estimation and / or the distance estimation. EST According to one embodiment, as better discussed below, the TOF device 100 may be intended to provide a TOF estimate and / or distance estimate D provided by the TOF device 100. EST Part of an electronic system to determine additional information.

[0044] Examples of additional information include, but are not limited to, displacement information, level information, material information, structural information, vibration information, and medical diagnostic information.

[0045] For the purposes of this disclosure, a target body T (which is not part of the TOF device 100) includes a physical object having mass. Examples of target bodies include, but are not limited to, living things (such as humans, animals, and trees) or parts thereof, and inanimate objects (such as buildings and vehicles) or parts thereof.

[0046] According to one embodiment, the TOF device 100 includes an ultrasonic transducer 105. According to one embodiment, the ultrasonic transducer 105 includes a piezoelectric ultrasonic transducer or a capacitive ultrasonic transducer.

[0047] According to one embodiment, the ultrasonic transducer 105 is configured to convert a power supply signal ESS (eg, a pulse width modulated pulse sequence) into an ultrasonic source signal USS, and convert an ultrasonic echo signal UES from the target volume T to obtain a corresponding electrical echo signal EES.

[0048] According to one embodiment, the power supply signal ESS and the electrical echo signal EES are digital signals, and the ultrasonic transducer 105 includes, for example, a conditioning and conversion system (not shown), which is used to obtain an analog ultrasonic source signal to be converted into the electrical echo signal EES from the (digital) power supply signal ESS, and to obtain a (digital) electrical echo signal EES from the converted ultrasonic echo signal.

[0049] According to one embodiment, the TOF device 100 comprises a processing unit 110 (eg a microcontroller and / or a microprocessor) electrically coupled to the ultrasound transducer 105 for providing an electrical supply signal ESS thereto and for receiving an electrical echo signal EES therefrom.

[0050] Hereinafter, only relevant modules of the processing unit 110 that are considered relevant to understanding the present disclosure will be discussed, and known and / or obvious variations of the relevant modules are omitted for the sake of brevity.

[0051] The term "module" is intended herein to emphasize its functionality (rather than implementation). In practice, without loss of generality, each module may be implemented by software, hardware, and / or a combination thereof, depending on its functionality. Furthermore, a module (or at least a subset thereof) may also reflect, at least conceptually, the physical structure of a processing unit. In any case, it should be understood that one or more of the modules shown may be integrated together into a single electronic unit.

[0052] According to one embodiment, the processing unit 110 comprises a module 115 for determining a noise power NP (or an indication thereof) associated with the electrical echo signal EES.

[0053] According to one embodiment, in order to determine the noise power NP associated with the electrical echo signal EES (or an indication thereof), the module 115 is configured to process the electrical echo signal EES according to a Fourier transform. In the description herein, the module 115 is also referred to as a Fourier module 115 .

[0054] According to one embodiment, the processing unit 110 comprises a signal for determining an envelope signal EES indicative of an envelope (eg a profile) of the electrical echo signal. ENV Module 120.

[0055] According to one embodiment, in order to determine the envelope signal EES ENV The module 120 is configured to process the electrical echo signal EES according to a Hilbert transform. In the description herein, the module 120 is also referred to as a Hilbert module 120 .

[0056] Since the envelope signal EES ENV The frequency of is less than the frequency of the electrical echo signal EES, so the envelope signal EES can be appropriately sampled in the form of samples / second without violating the Nyquist requirement. ENV Thus, the Hilbert module 120 performs a first signal "dilution" without losing information content, which determines a low computational request for the processing unit 110. Merely as an example, the frequency of the electrical echo signal EES may be approximately 400 KHz and the envelope signal EES ENV The frequency can be about 25KHz.

[0057] According to one embodiment, the processing unit 110 comprises a signal processing unit for determining the envelope signal EES. ENV In the description herein, the module 125 is also referred to as the partial module 125 and the envelope signal EES ENV This part is also called the envelope signal part EES ENVp .

[0058] According to one embodiment, the envelope signal portion EES ENVp Including envelope signal EES ENV The EES includes the envelope signal ENV The maximum value portion, that is, the envelope signal EES located to the left of the maximum value ENV The part (hereinafter referred to as the envelope signal EES ENV The left part of the maximum value) and the envelope signal EES to the right of the maximum value ENV The part (hereinafter referred to as envelope signal EES) ENV The right part of the envelope signal EES. ENV The left part and envelope signal EES ENV The right side of the envelope signal EES may have the same time length as, for example,ENV The portion of the envelope signal EES ENV The maximum value is centered, or may have a different time length, for example, the envelope signal EES ENV The portion does not contain an envelope signal EES ENV The maximum value is the center.

[0059] Since the envelope signal part EES ENVp is the envelope signal EES ENV part of the envelope signal, therefore, the EES ENVp can be quickly processed by subsequent modules of the processing unit 110 (to obtain a fast TOF estimate, and thus a fast distance estimate D EST ). The partial module 125 thus performs a second “dilution” of the signal without loss of information content, which determines a low computational requirement for the processing unit 110 .

[0060] Due to the low computational requirements of the processing unit 110 , the processing unit 110 may be a conventional microcontroller available on the market.

[0061] According to one embodiment, the envelope signal portion EES ENVp is determined based on one or more operating parameters.

[0062] Examples of operational parameters include, but are not limited to:

[0063] Indicator envelope signal EES ENV In other words, the first operating parameter Perc_1 indicates the maximum length of the left part of the envelope signal EES. ENV The left part of is an allowed range on the abscissa axis (ie, in time), and may depend, for example, on the processing capabilities of subsequent modules of the processing unit 110 and / or other design options;

[0064] Indicator envelope signal EES ENV In other words, the second operating parameter Perc_u indicates the maximum length of the right part of the envelope signal EES. ENV The right part of the envelope signal EES is in the abscissa axis (i.e., in time) and may depend, for example, on the processing capabilities of subsequent modules of the processing unit 110 and / or other design options (thus, the first operating parameter and the second operating parameter indicate the envelope signal portion EES ENVp maximum length in time);

[0065] Indicator envelope signal EES ENVIn other words, the third operating parameter Coeff1 indicates the envelope signal EES ENV The left side of the optimized range on the horizontal axis (ie, in time) is smaller than the allowed range. Compared with the allowed range, the envelope signal EES ENV The optimized length of the left portion of can further reduce the computations required by subsequent modules of the processing unit 110 without losing information content;

[0066] Indicator envelope signal EES ENV In other words, the fourth operating parameter Coeff2 indicates the envelope signal EES. ENV The right side of the optimized range on the horizontal axis is smaller than the allowable range. Therefore, the third operating parameter Coeff1 and the fourth operating parameter Coeff2 indicate the envelope signal portion EES ENVp The optimal length in time. Compared to the allowed range, the envelope signal EES ENV The optimized length of the right part of can further reduce the computations required by subsequent modules of the processing unit 110 without losing information content.

[0067] Hereinafter, when distinguishing between the first operating parameter, the second operating parameter, the third operating parameter, and the fourth operating parameter is irrelevant to understanding the present disclosure, the operating parameter will be globally denoted as OP k , where k denotes the number of iterations of the TOF method. Indeed, as better discussed below, according to one embodiment, the operating parameters or at least a subset thereof are adjusted or modified or updated at each iteration of the TOF method.

[0068] According to one embodiment, the operating parameters, or a subset thereof, are determined according to particle swarm optimization, as discussed in detail herein.

[0069] According to one embodiment, the partial module 125 (discussed better below) is configured to apply, in a first stage, a first operating parameter Perc_1 and a second operating parameter Perc_u to the envelope signal EES. ENV And in the second stage (after the first stage), the third operating parameter Coeff1 and the fourth operating parameter Coeff2 are applied to the envelope signal EES ENV (aimed at optimizing the envelope signal part EES ENVp The length of the envelope signal EES is determined by ENVp .

[0070] According to one embodiment, the processing unit 110 comprises a method for processing the envelope signal portion EES according to an unscented Kalman filter ENVpand a module 130 for determining the noise power NP of the electrical echo signal EES (that is why the module 130 will be referred to as UKF (“Unscented Kalman Filter”) module 130 in the following).

[0071] A Kalman filter is an algorithm that uses a series of measurements observed over time that contain statistical noise and other inaccuracies and produces estimates of unknown variables by estimating the joint probability distribution of the variables at each time interval. These estimates tend to be more accurate than estimates based on any single measurement alone.

[0072] The Kalman filter keeps track of the estimated state of the system and the variance, or uncertainty, of the estimate. It updates the estimate using a state transition model and measurements.

[0073] The algorithm works in two steps. In the prediction step, the Kalman filter generates estimates of the current state variables and their uncertainties. Once the results of the next measurement (which may be corrupted by a certain amount of error, including random noise) are observed, these estimates are updated using a weighted average, where estimates with greater certainty are given greater weight. The algorithm is recursive. It can run in real time using only the current input measurements and the previously calculated state and its uncertainty matrix; no additional past information is required.

[0074] The Unscented Kalman Filter is a generalization of the Kalman filter that is applicable to nonlinear systems. In the UKF, the probability density is approximated by a deterministic sampling of points that represent the underlying distribution as a Gaussian distribution. A nonlinear transformation of these points (called an unscented transformation) is intended to be an estimate of the posterior distribution, whose moments can then be derived from the transformed samples.

[0075] According to one embodiment, the UKF module 130 is configured to process the envelope signal portion EES based on one or more UKF parameters ENVp and the noise power NP of the electrical echo signal (the UKF parameters or a subset thereof are determined according to particle swarm optimization, as better discussed below).

[0076] Examples of UKF parameters include, but are not limited to, an evaluation parameter ("to_md_capture") that provides a first rough estimate of the TOF estimate (in order to provide a good starting point for the UKF module 130), a control parameter ("Kappa_p") for controlling the spread of the sigma point around the mean state value, and a correction parameter ("powerNoiseCorr") that provides a correction for the noise power NP. In some embodiments, the correction parameter is, for example, an additive correction factor to be added to the noise covariance matrix associated with the electrical echo signal EES. In other words, the "to_md_capture" parameter indicates an approximate estimate of the time of flight used as a starting point for the time of flight calculation and is proportional to x_max_inv-3σ, where x_max_inv is described below and σ is the value of the approximate envelope signal portion EES. ENVp The "Kappa_p" parameter indicates the spread of the sigma points around the mean value of the UKF state variable.

[0077] As described in the paper, the UKF parameters will be globally denoted as UKFP k , where k represents the number of iterations of the TOF method. As discussed further herein, according to one embodiment, the UKF parameters are adjusted or adjusted or updated at each iteration of the TOF method.

[0078] According to one embodiment, the UKF module 130 is configured to process the envelope signal portion EES ENVp The envelope signal EES is obtained by adding the noise power NP of the electric echo signal EES ENV Estimation of the envelope signal (hereinafter referred to as the envelope signal estimate EES ENVest According to one embodiment, the envelope signal estimate EES ENVest is the envelope signal part EES ENVp Regenerated, envelope signal EES ENV (see, e.g., L. Angrisani, A. Baccigalupi, R. Schiano Lo Moriello, “Ultrasonic time-of-flight estimation through unscented Kalman filter,” IEEE Transactions on Instrumentation and Measurement, August 2006).

[0079] According to one embodiment, the processing unit 110 comprises a signal processing unit for estimating the EES from the envelope signal ENVest A module for determining a TOF estimate (hereinafter referred to as an evaluation module) 135 is provided.

[0080] According to one embodiment, TOF estimation is based on the following discrete-time expression that models the ultrasound signal envelope (see, e.g., L. Angrisani, A. Baccigalupi, R. Schiano Lo Moriello, “Ultrasonic time-of-flight estimation through unscented Kalman filter”, IEEE Transactions on Instrumentation and Measurement, August 2006):

[0081]

[0082] in:

[0083] A0 is the amplitude of the electrical echo signal EES;

[0084] α and T are parameters that depend on the ultrasonic transducer used;

[0085] τ is the TOF estimate, and

[0086] t s is the sampling period.

[0087] According to one embodiment, the evaluation module 135 is configured to determine a distance estimate D between the target object T and the TOF device 100 based on the TOF estimate. EST .

[0088] According to one embodiment, the processing unit 110 comprises a module for determining the estimation error ε (hereinafter referred to as error module) 140. As better discussed below, the operating parameter OP k (or a subset thereof) and UKF parameters UKFP k (or a subset thereof) is determined according to a particle swarm optimization that receives the estimation error ε as input.

[0089] According to one embodiment, the estimated error ε determined at the error module 140 includes the distance estimate D between the TOF device 100 and the target body T. EST and distance D ACT As will be better understood from the following discussion, this embodiment allows for iterative adjustment, tuning, updating, or refinement of the operating parameter OP during a preliminary or calibration phase of the TOF device 100 (i.e., prior to using the TOF device 100 as a meter (e.g., a rangefinder)). k (or a subset thereof) and UKF parameters UKFP k(or a subset thereof). As better discussed below, a preliminary or calibration phase of the TOF device 100 is achieved by an embodiment of a TOF method (hereinafter referred to as an "offline TOF method"), wherein a ACT The known target volume T at the TOF device 100 is used to set the operating parameters OP that are subsequently used by the TOF device 100 when the TOF device 100 is used as an instrument (eg, a rangefinder). k and UKF parameters UKFP k .

[0090] According to one embodiment, the estimation error ε determined at the error module 140 comprises the envelope signal estimate EES ENVest With envelope signal EES ENV As will be better understood from the following discussion, this embodiment allows the operating parameter OP to be iteratively adjusted, modified, updated, or improved in real time during use of the TOF device 100 as an instrument (e.g., a rangefinder). k Subsets and UKF parameters UKFP k As better discussed below, this is obtained by an embodiment of a TOF method (hereinafter referred to as "online TOF method").

[0091] According to one embodiment, the TOF device 100 may be configured to implement an offline TOF method (in this case, the distance estimation D EST and distance D ACT received at the error module 140) or an online TOF method (in this case, the envelope signal EES ENV and envelope signal estimation EES ENVest received at the error module 140) or both offline and online TOF methods (e.g., using an online TOF method that can be followed by an offline TOF method): the possibility of implementing an offline TOF method and / or an online TOF method is Figure 1 The distance D from the input to the error module 140 is estimated EST , distance D ACT , envelope signal EES ENV and envelope signal estimation EES ENVest The associated dashed arrows are conceptually represented.

[0092] According to one embodiment, the processing unit 110 comprises a module (hereinafter referred to as a swarm module) 145 for determining the operating parameter OP according to particle swarm optimization and based on the estimated error ε received as input to the error module 140. k (or operating parameter OP k subset) and UKF parameters UKFP k (or UKF parameter UKFPk subset of ).

[0093] Particle swarm optimization is a computational method that optimizes a problem by iteratively attempting to improve candidate solutions relative to a given quality metric. It solves the problem by having a set of candidate solutions, called particles, and moving these particles around a search space according to a simple mathematical formula on their positions and velocities. Each particle's movement is influenced by its local best known position, but is also guided towards the best known positions in the search space, which are updated as other particles find better positions.

[0094] The main equation of particle swarm optimization is as follows:

[0095] C i，j =c1r 1，j (p i，j (t-1)-x i，j (t-1))

[0096] S i，j =c2r 2，j (g i，j (t-1)-x i，j (t-1))

[0097] V i，j (t)=wV i，j (t-1)+C i，j +S i，j

[0098] x i，j (t) = x i，j (t-1)+Vi,j(t)

[0099] in:

[0100] p i，j is the local optimum of the i-th particle;

[0101] g i，j is the global optimum of the i-th particle in the current neighborhood;

[0102] C i，j is the i-th cognitive parameter in the j-dimensional search space;

[0103] S i，j is the i-th social parameter in the j-dimensional search space;

[0104] V i，j (t) is the velocity parameter of the i-th particle in the j-dimensional search space;

[0105] x i，j (t) is the position (solution) of the i-th particle in the j-dimensional search space;

[0106] r 1，j 、r 2，j is a uniformly distributed random value in [0, 1];

[0107] c1, c2 are the acceleration coefficients of the cognitive component and the social component respectively; and

[0108] w is the inertia weight designed to judge the exploration phase and the development phase.

[0109] Figure 2A An offline TOF method 200 according to an embodiment of the present disclosure is shown. A Activity diagram.

[0110] According to one embodiment, the offline TOF method 200 A This is achieved by appropriate software instructions stored in or accessible by the TOF device 100 and / or by appropriate hardware / firmware of the TOF device 100 .

[0111] According to one embodiment, the offline TOF method 200 A The ultrasonic echo signal UES is acquired to obtain the corresponding electrical echo signal EES (action node 205 ). According to one embodiment, the ultrasonic echo signal UES is acquired at a conditioning and conversion system (not shown) of the ultrasonic transducer 105 to obtain the corresponding electrical echo signal EES.

[0112] According to one embodiment, the offline TOF method 200 A It comprises determining the noise power NP of the electrical echo signal EES (action node 210 ). According to one embodiment, the noise power NP of the electrical echo signal EES is determined at the Fourier module 115 of the processing unit 110 .

[0113] According to one embodiment, the offline TOF method 200 A Including determining the envelope signal EES ENV (Action node 215 ). According to one embodiment, the envelope signal EES is determined at the Hilbert module 120 of the processing unit 110 ENV .

[0114] According to one embodiment, the offline TOF method 200 A Including the EES part of the envelope signal ENVp (Action node 220). According to one embodiment, the envelope signal portion EES is determined at the part module 125 of the processing unit 110. ENVp According to one embodiment, the operating parameter OP generated based on the particle swarm optimization performed in the previous (k-1)th iteration before the current kth iteration k To determine the envelope signal part EESENVp According to one embodiment, in the offline TOF method 200 A During the first run (k=0), the operation parameter adjustment based on particle swarm optimization has not yet occurred, and the operation parameter OP k The default value is set, for example, by the manufacturer based on design experience.

[0115] According to one embodiment, the offline TOF method 200 A Including EES according to the envelope signal part ENVp The sum of the noise power NP determines the envelope signal estimation EES ENVest (Action node 225). According to one embodiment, the envelope signal portion EES is determined at the UKF module 130 of the processing unit 110 ENVp , as shown below Figure 4 According to one embodiment, the UKF parameter UKFP generated based on the particle swarm optimization performed in the previous (k-1)th iteration before the current kth iteration is k To determine the envelope signal estimate EES ENVest According to one embodiment, in the offline TOF method 200 A During the first run (k=0), the UKF parameter adjustment based on particle swarm optimization has not yet occurred, and the UKF parameter UKFP k The default value is set, for example, on the manufacturer's side based on designer experience.

[0116] According to one embodiment, the offline TOF method 200 A Including estimation of EES based on envelope signal ENVest Determine a TOF estimate and determine a distance estimate D based on the TOF estimate EST (Action node 230). According to one embodiment, the TOF estimate and the distance estimate D are determined at the evaluation module 135 of the processing unit 110. EST .

[0117] According to one embodiment, the offline TOF method 200 A This involves determining the estimation error ε as the distance estimate D EST and distance D ACT The difference between (action node 235 A According to one embodiment, the estimation error ε is determined at the error module 140 of the processing unit 110 .

[0118] According to one embodiment, the offline TOF method 200 A As long as the estimation error ε is higher than the threshold estimation error ε TH , iteratively adjust and improve the operating parameters OP kand UKF parameters UKFP k (or a subset thereof). According to one embodiment, if the estimation error ε is higher than a threshold estimation error ε TH (exit branch N of decision node 240), the subsequent iteration begins (k=k+1, action node 245), and the operating parameter OP is adjusted at the swarm module 145 of the processing unit 110 based on the estimated error ε received as input to the error module 140 and based on the particle swarm optimization k and UKF parameters UKFP k .

[0119] According to one embodiment, as long as the estimation error ε is higher than a threshold estimation error ε TH , just repeat nodes 220-250.

[0120] Returning to decision node 240, according to one embodiment, if the estimation error ε is lower than the threshold estimation error ε TH (Exit branch Y of decision node 240), which represents the operating parameter OP k and UKF parameters UKFP k has been optimized, then the optimized operating parameters OP are appropriately stored k and optimized UKF parameters UKFP k (Action Node 255) for Offline TOF Method 200 A A subsequent run of the TOF method (or a subsequent run for an online TOF method) and then an offline TOF method 200 A Finish.

[0121] Offline TOF methods can be useful in the design phase, where TOF estimates are determined with high accuracy from a set of signals under known measurement conditions in a supervised manner. The applicant has experimentally determined that a TOF device with operating and UKF parameters optimized using the offline TOF method is capable of managing a very large number of shaped ultrasound echo signals at distances of 0.30 m to 2 m with an average accuracy of less than 3 mm.

[0122] Figure 2B An online TOF method 200 according to an embodiment of the present disclosure is shown. B Activity diagram.

[0123] According to one embodiment, the online TOF method 200 B This is achieved by appropriate software instructions stored in or accessible by the TOF device 100 and / or by appropriate hardware / firmware of the TOF device 100 .

[0124] According to one embodiment, the online TOF method 200 BThe ultrasonic echo signal UES is acquired to obtain the corresponding electrical echo signal EES (action node 205 ). According to one embodiment, the ultrasonic echo signal UES is acquired at a conditioning and conversion system (not shown) of the ultrasonic transducer 105 to obtain the corresponding electrical echo signal EES.

[0125] According to one embodiment, the online TOF method 200 B It comprises determining the noise power NP of the electrical echo signal EES (action node 210 ). According to one embodiment, the noise power NP of the electrical echo signal EES is determined at the Fourier module 115 of the processing unit 110 .

[0126] According to one embodiment, the online TOF method 200 B Including determining the envelope signal EES ENV (Action node 215 ). According to one embodiment, the envelope signal EES is determined at the Hilbert module 120 of the processing unit 110 ENV .

[0127] According to one embodiment, the online TOF method 200 B Including the EES part of the envelope signal ENVp (Action node 220). According to one embodiment, the envelope signal portion EES is determined at the part module 125 of the processing unit 110. ENVp According to one embodiment, the operating parameter OP generated based on the particle swarm optimization performed in the previous (k-1)th iteration before the current kth iteration k A subset of the envelope signal to determine the EES ENVp According to one embodiment, in the online TOF method 200 B During the first run (k=0), the operation parameter adjustment based on particle swarm optimization has not yet occurred, and the operation parameter OP k The subset of is at a default value, which is determined, for example, on the manufacturer's side, for example based on designer experience, or in the online TOF method 200 B Previously performed offline TOF method (such as offline TOF method 200 A ) is determined at .

[0128] According to one embodiment, the operating parameter OP k The subset includes but is not limited to the third operating parameter Coeff1 and the fourth operating parameter Coeff2 (ie, indicating the envelope signal EES ENV The optimized length of the left part and the optimized length of the right part, and thus indicates the envelope signal portion EES ENVp=The operating parameters of the optimized total length on the abscissa axis). In fact, the applicant has experimentally determined that the first operating parameter Perc_l and the second operating parameter Perc_u (especially when they are in the online TOF method 200 B Previous offline TOF methods (such as offline TOF method 200 A ) period is adjusted) is sufficiently effective to allow identification (together with the online method 200 B The third operating parameter Coeff1 and the fourth operating parameter Coeff2 adjusted during the optimal envelope signal portion EES ENVp .

[0129] According to one embodiment, the online TOF method 200 B Including EES according to the envelope signal part ENVp and noise power NP to determine the envelope signal estimation EES ENVest (Action node 225). According to one embodiment, the envelope signal portion EES is determined at the UKF module 130 of the processing unit 110 ENVp , as shown below Figure 4 According to one embodiment, the UKF parameter UKFP generated based on the particle swarm optimization performed in the previous (k-1)th iteration before the current kth iteration is k A subset of the envelope signal is used to determine the EES ENVest According to one embodiment, in the online TOF method 200 B During the first run (k=0), the UKF parameter adjustment based on particle swarm optimization has not yet occurred, and the UKF parameter UKFP k The subset of is at default values, which are determined, for example, on the manufacturer's side, for example based on designer experience.

[0130] According to one embodiment, the UKF parameter UKFP k The subset of includes but is not limited to evaluation parameters and control parameters. In fact, the applicant has experimentally determined that some parameters, such as correction parameters, do not affect (or substantially do not affect) TOF estimation. Therefore, according to one embodiment, the correction parameters (especially when they are used in the online TOF method 200) B Previous offline TOF methods (such as offline TOF method 200 A ) is adjusted during the online TOF method 200 B The period is no longer adjusted.

[0131] According to one embodiment, the online TOF method 200 B This involves determining the estimation error ε as the envelope signal estimate EES ENVest With envelope signal EES ENVThe difference between (action node 235 B According to one embodiment, the estimation error ε is determined at the error module 140 of the processing unit 110 .

[0132] According to one embodiment, the online TOF method 200 B As long as the estimation error ε is higher than the threshold estimation error ε TH , iteratively adjust and improve the operating parameters OP k Subsets and UKF parameters UKFP k According to one embodiment, if the estimation error ε is higher than a threshold estimation error ε TH (exit branch N of decision node 240), the subsequent iteration begins (k=k+1, action node 245), and the operating parameter OP is adjusted at the swarm module 145 of the processing unit 110 based on the estimated error ε received as input to the error module 140 and based on the particle swarm optimization k Subsets and UKF parameters UKFP k A subset of .

[0133] According to one embodiment, as long as the estimation error ε is higher than a threshold estimation error ε TH , just repeat nodes 220-250.

[0134] Returning to decision node 240, according to one embodiment, if the estimation error ε is lower than the threshold estimation error ε TH (Exit branch Y of decision node 240), which represents the operating parameter OP k Subsets and UKF parameters UKFP k The subset of has been optimized, then the EES is estimated based on the envelope signal ENVest (i.e., based on the operating parameter OP k The optimized subset and UKF parameters UKFP k Envelope signal estimation EES determined by the optimized subset ENVest ) to determine the TOF estimate, and to determine the distance estimate D based on the TOF estimate EST (Action node 230). According to one embodiment, the TOF estimate and the distance estimate D are determined at the evaluation module 135 of the processing unit 110. EST .

[0135] According to one embodiment, the operating parameters OP are appropriately stored. k The optimized subset and UKF parameters UKFP k Optimized subset (action node 255) for online TOF method 200 B Subsequent operation of .

[0136] The online TOF method provides TOF estimation that dynamically and automatically adapts to different external conditions.

[0137] For example, the offline TOF method 200 A and online TOF method 200 B The training data set includes, for example, 160 ultrasonic echo signals (e.g., 135 for offline adjustment and 25 for testing online adjustment), the 160 ultrasonic echo signals indicating a distance between the target object T and the TOF device 100 ranging from approximately 0.3 m to approximately 2 m and acquired at a sampling rate of approximately 400 kS / s. In particular, the 25 ultrasonic echo signals used for testing online adjustment were acquired under various operating conditions (e.g., variable temperature, humidity, wind speed, etc.).

[0138] Now refer to Figure 3 , Figure 3 A simplified block diagram of an electronic system 300 (ie, a portion thereof) including a TOF device 100 (or multiple TOF devices 100) according to an embodiment of the present disclosure is shown.

[0139] According to one embodiment, the electronic system 300 is applicable to an electronic device.

[0140] According to one embodiment, the electronic system 300 includes a controller 305 (eg, one or more microprocessors and / or one or more microcontrollers).

[0141] According to one embodiment, the electronic system 300 includes an input / output device 310 (e.g., a keyboard and / or a screen). The input / output device 310 can, for example, be used to generate and / or receive messages. The input / output device 310 can, for example, be configured to receive / provide digital signals and / or analog signals.

[0142] According to one embodiment, the electronic system 300 includes a wireless interface 315 for exchanging messages with a wireless communication network (not shown), such as via radio frequency signals. Examples of a wireless interface may include an antenna and a wireless transceiver.

[0143] According to one embodiment, the electronic system 300 includes a power supply device (eg, a battery 320 ) for supplying power to the electronic system 300 .

[0144] According to one embodiment, the controller 305 (or one or more dedicated computing units, not shown) can be configured to determine additional information (e.g., displacement information, level information, material information, structural information, vibration information, and medical diagnostic information) based on the distance information provided by the TOF device 100.

[0145] According to one embodiment, the electronic system 300 includes one or more communication channels (buses) 325 to allow data exchange between the TOF device 100, the controller 305 (when provided), the input / output device 310 (when provided), the wireless interface 315 (when provided), and the power supply device 320 (when provided).

[0146] Figure 4 1 shows an activity diagram of a signal cutting method 400 according to an embodiment of the present invention. The signal cutting method 400 allows the envelope signal EES to be cut during use of the TOF device 100 by applying operating parameters to the envelope signal EES. ENV To determine the envelope signal part EES ENVp .

[0147] According to one embodiment, the signal cutting method 400 is implemented by appropriate software instructions stored in or accessible by the TOF device 100 and / or by appropriate hardware / firmware of the TOF device 100. In particular, the signal cutting method 400 is implemented by the partial module 125.

[0148] In detail, the signal cutting method 400 comprises determining the envelope signal EES according to a technique known per se. ENV The maximum value of (action node 405), that is, including the calculation of the envelope signal EES ENV The maximum value max_inv and the maximum value max_inv in the envelope signal EES ENV The first time position x_max_inv in (on the abscissa axis, ie in time; also called the first instant x_max_inv).

[0149] The signal cutting method 400 includes calculating the envelope signal EES by using a first operating parameter Perc_1 and a second operating parameter Perc_u. ENV The first threshold thresh1 and the second threshold thresh2 are smaller than the maximum value max_inv (action node 410). In detail, the first threshold thresh1 is related to the envelope signal EES. ENV The maximum length of the left part of the envelope signal EES ENV The second threshold thresh2 is the same as the envelope signal EES. ENV The maximum length of the right part of the envelope signal EES ENV In other words, the envelope signal EES ENV The left side portion includes the envelope signal EES ranging from a first threshold value thresh1 to a maximum value max_inv ENV The value of the envelope signal EES ENVThe right part of includes the envelope signal EES ranging from the maximum value max_inv to the second threshold value thresh2. ENV In more detail, based on the envelope signal EES ENV The first threshold thresh1 and the second threshold thresh2 are respectively calculated (particularly, depending on the product thereof) by using the maximum value max_inv of the first operating parameter Perc_1 and the second operating parameter Perc_u. Particularly, thresh1=Perc_1·max_inv and thresh2=Perc_u·max_inv.

[0150] The signal cutting method 400 further includes determining a first threshold thresh1 at the envelope signal EES. ENV The second time position x_thresh1 (on the abscissa axis, ie, in time; also called the second instant x_max_inv) and the second threshold value thresh2 in the envelope signal EES ENV The third time position x_thresh2 (on the abscissa axis, ie, in time; also referred to as the third moment x_max_inv) in the second time position x_thresh1 and the third time position x_thresh2 are respectively associated with the envelope signal EES. ENV The maximum length of the left part and the maximum length of the right part are related. The first time position x_thresh1 and the second time position x_thresh2 are respectively the envelope signal EES ENV The envelope signal EES presents a first threshold value thresh1 and a second threshold value thresh2 ENV and are respectively located before and after the first time position x_max_inv (i.e., to the left and right of the first time position x_max_inv on the time scale). In other words, x_thresh1=x_max_inv-Δ1 and x_thresh2=x_max_inv-Δ2, where Δ1 and Δ2 are respective time intervals whose lengths correspond to the envelope signal EES, respectively. ENV The maximum time length of the left part and the maximum time length of the right part. Therefore, the envelope signal EES ENV The left side portion of is at most between the second time position x_thresh1 and the first time position x_max_inv, and the envelope signal EES ENV The right side portion of is at most between the first time position x_max_inv and the third time position x_thresh2.

[0151] Therefore, according to one embodiment, the envelope signal portion EES ENVpincluding (specifically, in accordance with it) an envelope signal EES included between a second time position x_thresh1 and a third time position x_thresh2 ENV portion.

[0152] Optionally, according to different embodiments, the signal cutting method 400 further includes optimizing the envelope signal portion EES by calculating a fourth time position x_opt1 (on the horizontal axis, i.e., in time; also referred to as the fourth moment x_max_inv) and a fifth time position x_opt2 (on the horizontal axis, i.e., in time; also referred to as the fifth moment x_max_inv) of the envelope signal EES via a third operation parameter Coeff1 and a fourth operation parameter Coeff2 ENV (action node 420). The fourth time position x_opt1 is greater than the second time position x_thresh1 and depends on the second time position x_thresh1 and the third operation parameter Coeff1, and the fifth time position x_opt2 is less than the third time position x_thresh2 and depends on the third time position x_thresh2 and the fourth operation parameter Coeff2. In this embodiment, the envelope signal portion EES ENVp includes (specifically, in accordance with it) an envelope signal including an envelope signal EES included between the fourth time position x_opt1 and the fifth time position x_opt2 ENVp portion. In other words, the fourth time position x_opt1 and the fifth time position x_opt2 respectively indicate the optimized lengths of the left portion and the right portion of the envelope signal EES ENV . Specifically, x_thresh1 < x_opt1 < x_max_inv and x_max_inv < x_opt2 < x_thresh2. More specifically, the third operation parameter Coeff1 and the fourth operation parameter Coeff2 indicate the respective time offsets to be applied to the second time position x_thresh1 and the third time position x_thresh2 to obtain the fourth time position x_opt1 and the fifth time position x_opt2. In other words, x_opt1 = x_thresh1 + Coeff1 and x_opt2 = x_thresh2 - Coeff2, where Coeff1 < Δ1 and Coeff2 < Δ2. Therefore, in the current case, the optimized left portion of the envelope signal EES ENV is between the fourth time position x_opt1 and the first time position x_max_inv, and the optimized right portion of the envelope signal EES ENV is between the first time position x_max_inv and the fifth time position x_opt2. ENV

[0153] Figure 5 FIG2 shows an activity diagram of a time-of-flight estimation method 500 according to an embodiment of the present invention. The time-of-flight estimation method 500 allows estimating the flight time between an ultrasound signal emitted by a TOF device 100 and an ultrasound echo signal returned by a target object T struck by the ultrasound signal and received at the TOF device 100.

[0154] According to one embodiment, the time of flight estimation method 500 is implemented by appropriate software instructions stored in or accessible by the TOF device 100 and / or by appropriate hardware / firmware of the TOF device 100 .

[0155] According to one embodiment, the time-of-flight estimation method 500 includes acquiring an ultrasonic echo signal UES to obtain a corresponding electrical echo signal EES (action node 505). According to one embodiment, acquiring the ultrasonic echo signal UES to obtain the corresponding electrical echo signal EES is performed at a conditioning and conversion system (not shown) of the ultrasonic transducer 105.

[0156] According to one embodiment, the time of flight estimation method 500 comprises determining the noise power NP of the electrical echo signal EES (action node 510 ). According to one embodiment, the noise power NP of the electrical echo signal EES is determined at the Fourier module 115 of the processing unit 110 .

[0157] According to one embodiment, the time-of-flight estimation method 500 comprises determining an envelope signal EES ENV (Action node 515 ). According to one embodiment, the envelope signal EES is determined at the Hilbert module 120 of the processing unit 110 ENV .

[0158] According to one embodiment, the time of flight estimation method 500 comprises determining the envelope signal portion EES according to the signal segmentation method 400 described previously. ENVp (Action node 400). According to one embodiment, based on the offline TOF method 200 at the partial module 125 of the processing unit 110 A or online TOF method 200 B The resulting operating parameters OP k Determine the envelope signal portion EES ENVp .

[0159] According to one embodiment, the flight time estimation method 500 includes: ENVp and noise power NP to determine the envelope signal estimation EES ENVest (Action node 525). According to one embodiment, at the UKF module 130 of the processing unit 110, based on the offline TOF method 200A or online TOF method 200 B Generated UKF parameters UKFP k To determine the envelope signal part EES ENVp .

[0160] According to one embodiment, the time-of-flight estimation method 500 includes estimating the EES based on the envelope signal ENVest Determine a TOF estimate and determine a distance estimate D based on the TOF estimate EST (Action node 530). According to one embodiment, the TOF estimate and the distance estimate D are determined at the evaluation module 135 of the processing unit 110. EST .

[0161] From an examination of the features of the present invention as made according to the invention, the advantages it allows are clear.

[0162] The signal segmentation method 400 reduces the computational cost required for estimating the time of flight by the time of flight estimation method 500 , in particular by reducing the computational cost of the UKF module 130 .

[0163] The envelope signal portion EES output by the action node 415 ENVp It has been optimized for the UKF module 130. Nevertheless, the envelope signal portion EES is calculated according to the action node 420 ENVp This allows for further reduction of computational cost and improvement of time-of-flight estimation accuracy.

[0164] By offline TOF method 200 A To calculate the operating parameter OP k The optimized subset and UKF parameters UKFP k In addition, the online TOF method 200 B The third operating parameter Coeff1 and the fourth operating parameter Coeff2 are further optimized.

[0165] Finally, it is obvious that modifications and variations may be made to the invention described and illustrated herein without departing from the scope of the invention as defined in the appended claims. For example, the different embodiments described may be combined to provide further solutions.

[0166] A method (200A; 200B) for providing an estimate of the time of flight between an ultrasonic signal emitted by a device (100) and an ultrasonic echo signal returned by a target object (T) struck by the ultrasonic signal and received at the device, the method being summarized as comprising: acquiring (205) the ultrasonic echo signal to obtain an electrical echo signal; determining (210) a noise power of the electrical echo signal; determining (215) an envelope signal indicative of an envelope of the electrical echo signal; determining (220) a portion of the envelope signal based on at least one operating parameter (OPK), the at least one operating parameter being determined according to particle swarm optimization; processing (225) the portion of the envelope signal and the noise power of the electrical echo signal according to an unscented Kalman filter to obtain an estimate of the envelope signal, wherein the estimate of the envelope signal is a regenerated version of the envelope signal regenerated from the portion of the envelope signal, the processing being based on unscented Kalman filter parameters (UKF) determined according to the particle swarm optimization. k ); and providing (230) an estimate of the time of flight based on the estimate of the envelope signal. The method (200A; 200B) also includes determining (235A; 235B) an estimation error, wherein the particle swarm optimization is based on the estimation error.

[0167] The determining (235A; 235B) of the estimation error includes determining (235B) a difference between the estimate of the envelope signal and the envelope signal.

[0168] The method (200A; 200B) further comprises determining (230) a distance estimate indicative of a distance between the target object (T) and the device (100) based on the estimate of the time of flight, wherein determining (235A; 235B) an estimated error comprises determining (235A) a difference between the distance estimate and the distance.

[0169] Said determining (215) an envelope signal may comprise performing a Hilbert transform on said electrical echo signal.

[0170] The portion of the envelope signal is centered around a maximum value of the envelope signal.

[0171] Part of the operation of processing (225) the envelope signal may include providing a regenerated envelope signal.

[0172] The at least one operating parameter (OP K ) includes at least one of the following: an operating signal indicating a maximum length of the portion of the envelope signal in time, and an optimized length of the portion of the envelope signal in time, the optimized length being less than the maximum length.

[0173] The at least one unscented Kalman filter parameter (UKFP K ) may include at least one of the following: an evaluation parameter providing a rough estimate of the flight time; a control parameter for controlling the extension of the sigma point around the mean state value; and a correction parameter providing a correction for the noise power of the electrical echo signal.

[0174] A device (100) for providing an estimate of the time of flight between an ultrasonic signal emitted by the device and an ultrasonic echo signal returned by a target object (T) struck by the ultrasonic signal and received at the device, the device being summarized as comprising: a conditioning and conversion system (105) for acquiring the ultrasonic echo signal to obtain an electrical echo signal; a module (115) for determining the noise power of the electrical echo signal; a module (120) for determining an envelope signal indicative of the envelope of the electrical echo signal; a module (125) for determining the envelope of the electrical echo signal based on at least one operating parameter (OP) K ) determines a portion of the envelope signal, the at least one operating parameter being determined according to particle swarm optimization; a module (130) for processing the portion of the envelope signal and the noise power of the electrical echo signal according to an unscented Kalman filter to obtain an estimate of the envelope signal, wherein the estimate of the envelope signal is a regenerated version of the envelope signal regenerated from the portion of the envelope signal, the processing being based on at least one unscented Kalman filter parameter (UKF) determined according to the particle swarm optimization K ), and a module (135) for providing said estimate of said time of flight based on an estimate of said envelope signal.

[0175] The various embodiments described above can be combined to provide further embodiments. Aspects of the embodiments can be modified, if necessary, to employ concepts from the various embodiments to provide still further embodiments.

[0176] These and other changes can be made to the embodiments in light of the above detailed description. In general, in the following claims, the terms used should not be construed to limit the claims to the specific embodiments disclosed in the specification and claims, but should be construed to encompass all possible embodiments and the full scope of equivalents to which the claims are entitled. Therefore, the claims are not limited by this disclosure.

Claims

1. A method for providing an estimate of the time of flight between an ultrasound signal and an ultrasound echo signal, the ultrasound signal being emitted by a device, the ultrasound echo signal returning from a target object struck by the ultrasound signal and being received at the device, the method comprising: acquiring the ultrasonic echo signal; obtaining an electrical echo signal based on the ultrasonic echo signal; determining a noise power of the electrical echo signal; determining an envelope signal indicative of an envelope of the electrical echo signal; determining at least one operating parameter of the envelope signal based on particle swarm optimization; determining a portion of the envelope signal based on the at least one operating parameter; determining at least one unscented Kalman filter parameter of the unscented Kalman filter based on particle swarm optimization; processing the portion of the envelope signal and the noise power of the electrical echo signal according to the unscented Kalman filter to obtain an estimate of the envelope signal, the estimate of the envelope signal being a regenerated version of the envelope signal based on the portion of the envelope signal; as well as The estimate of the time of flight is provided based on the estimate of the envelope signal.

2. The method according to claim 1, further comprising: determining an estimation error between the estimate of the envelope signal and the envelope signal; The particle swarm optimization is determined based on the estimation error.

3. The method of claim 2 , wherein determining the estimation error comprises: A difference between the estimate of the envelope signal and the envelope signal is determined.

4. The method according to claim 2, further comprising: determining a distance estimate indicative of a distance between the target object and the device based on the estimate of the time of flight, in Determining an estimation error includes determining a difference between the distance estimate and the distance.

5. The method of claim 1 , wherein determining the envelope signal comprises: A Hilbert transform is performed on the electrical echo signal. The method of claim 1 , wherein the portion of the envelope signal is centered around a maximum value of the envelope signal.

7. The method of claim 1 , wherein processing the portion of the envelope signal comprises: Provides a regenerated envelope signal.

8. The method of claim 1 , wherein the at least one operating parameter comprises at least one of: a first operating parameter and a second operating parameter indicating a maximum length in time of said portion of said envelope signal, or A third operating parameter and a fourth operating parameter indicate an optimized length in time of the portion of the envelope signal, the optimized length being less than the maximum length.

9. The method of claim 8, wherein determining the portion of the envelope signal comprises: calculating a maximum value of the envelope signal and a corresponding first time position at which the envelope signal has the maximum value; Calculating a first threshold and a second threshold of the envelope signal respectively according to the first operating parameter, the second operating parameter and the maximum value of the envelope signal, wherein the first threshold and the second threshold are smaller than the maximum value of the envelope signal; as well as Determine a second time position of the envelope signal at which the value of the envelope signal is equal to the first threshold, and a third time position of the envelope signal at which the value of the envelope signal is equal to the second threshold, the second time position being smaller than the first time position, and the third time position being larger than the first time position.

10. The method of claim 9, wherein the portion of the envelope signal is defined as being between the second time position and the third time position.

11. The method of claim 9, wherein determining the portion of the envelope signal further comprises: calculating a fourth time position based on the third operating parameter and the second time position, and calculating a fifth time position based on the fourth operating parameter and the third time position, the fourth time position being greater than the second time position and less than the first time position, and the fifth time position being greater than the first time position and less than the third time position, and The portion of the envelope signal is defined as being between the fourth time position and the fifth time position.

12. The method of claim 1 , wherein the at least one unscented Kalman filter parameter comprises at least one of: Evaluate parameters to provide a rough estimate of the flight time; Control parameters for controlling the spread of sigma points around the mean state value; and A correction parameter provides a correction for the noise power of the electrical echo signal.

13. An apparatus for providing an estimate of the time of flight between an ultrasound signal transmitted by the apparatus and an ultrasound echo signal returned by a target object struck by the ultrasound signal and received at the apparatus, the apparatus comprising: a conditioning and conversion system for acquiring the ultrasonic echo signal and obtaining an electrical echo signal based on the ultrasonic echo signal; circuitry for determining noise power of the electrical echo signal; circuitry for determining an envelope signal indicative of an envelope of the electrical echo signal; circuitry for determining a portion of the envelope signal based on at least one operating parameter of the envelope signal, the at least one operating parameter being determined according to particle swarm optimization; circuitry for obtaining an estimate of the envelope signal by processing the portion of the envelope signal and the noise power of the electrical echo signal according to an unscented Kalman filter, the estimate of the envelope signal being based on a regenerated version of the envelope signal of the portion of the envelope signal, and at least one unscented Kalman filter parameter being determined according to the particle swarm optimization; as well as Circuitry for providing the estimate of the time of flight based on the estimate of the envelope signal.

14. The apparatus according to claim 13, further comprising: circuitry for determining an estimated error between the estimate of the envelope signal and the envelope signal; as well as Circuitry is configured to determine the particle swarm optimization based on the estimation error.

15. A method for flight time estimation, comprising: acquiring an electrical echo signal representing a time-of-flight signal from the device and reflected from the object; determining a noise power of the electrical echo signal; generating a first envelope signal indicative of an envelope of the electrical echo signal; determining a portion of the first envelope signal; generating a second envelope signal based on the portion of the first envelope signal and the noise power of the electrical echo signal using an unscented Kalman filter; calculating a time of flight of the time-of-flight signal based on the second envelope signal; as well as determining an operating parameter of the first envelope signal based on particle swarm optimization, wherein determining the portion of the first envelope signal comprises: determining the portion of the first envelope signal based on the operating parameter, The method further includes determining parameters of an unscented Kalman filter based on particle swarm optimization.

16. The method according to claim 15, comprising: determining an estimated distance indicating a distance between the object and the device based on the travel time; as well as A difference between the estimated distance and the distance is determined.

17. The method according to claim 15, wherein: The determining of the first envelope signal includes performing a Hilbert transform on the electrical echo signal.

18. The method of claim 15, wherein determining the portion of the first envelope signal comprises: The portion of the envelope signal centered around a maximum value of the first envelope signal is determined.

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