DE102018010260A1 - Classification of signal objects within ultrasonic reception signals and compressed transmission of symbols as representatives of these signal objects to a computer unit for object recognition - Google Patents

Abstract

A method is proposed for transmitting sensor data of an ultrasonic sensor from a sensor to a computer system in a vehicle. The method comprises the steps of a) transmitting an ultrasonic burst, and b) receiving an ultrasonic signal and forming a received signal, and c) forming a feature vector signal from the received signal, and d) detecting and classifying signal objects Signal objects in recognized signal object classes within the received signal, each signal object thus recognized and classified at least one associated signal object parameter and a symbol corresponding to the signal object class awarded to this signal object class or wherein each thus recognized and classified signal object at least one associated signal object parameter and a symbol for this signal object are determined , and e) transmitting at least the symbol of a recognized signal object class and at least the one associated signal object parameter of this detected signal object class to the computer system.

Description

The invention is directed to a method for transmitting data from an ultrasonic sensor system for parking aids in vehicles to a computer system and a corresponding device. The basic idea is the detection of potentially relevant structures in the measurement signal and the compression of this measurement signal by transmitting only these detected, potentially relevant structures instead of the measurement signal itself. The actual detection of objects, e.g. Obstacles for the parking process, takes place only after reconstruction of the measurement signal as a reconstructed measurement signal in the computer system, where typically several such decompressed measurement signals of several ultrasonic sensor systems come together. Here, the compression of the data is claimed by structure recognition in the measurement signal.

General introduction

Ultrasonic sensor systems for parking aids in vehicles are becoming increasingly popular. In this case, there is a desire to transmit more and more data of the actual measuring signal of the ultrasonic sensor to a central computer system, where this is combined with data from other ultrasonic sensor systems and also from other types of sensor systems, e.g. Radar systems, by sensor fusion to so-called environmental or environmental maps to be reworked. Therefore, there is a desire to perform object recognition not in the ultrasound sensor system itself, but only in the computer system through just this sensor fusion in order to avoid data losses and thus to reduce the probability of misinformation and thus incorrect decisions and thus accidents. At the same time, however, the transmission bandwidth of the available sensor data buses is limited. Their replacement should be avoided because they have proven themselves in the field. At the same time, therefore, there is a desire not to increase the amount of data to be transmitted. In short: The information content of the data and its relevance to the later in the computer system running obstacle detection (object recognition) must be increased without having to raise the data rate too much - better: without having to increase the data rate at all. Quite to the contrary: Preferably, the data rate requirement should even be lowered in order to allow data rate capacities for the transmission of status data and self-test information of the ultrasound sensor system to the computer system, which is imperative in the context of Functional Safety (FuSi). This problem is addressed by the disclosure presented here.

Various methods of processing an ultrasonic sensor signal are already known in the prior art.

From the WO 2012/016 834 A1 For example, such a method for evaluating an echo signal for vehicle environment detection is known. It is proposed there to emit a measurement signal with a predefinable coding and shape and to search in the received signal by means of a correlation with the measurement signal for the proportions of the measurement signal in the received signal and to determine these. The level of the correlation and not the level of the envelope of the echo signal is then evaluated with a threshold value.

From the DE 4 433 957 A1 It is known to radiate ultrasound pulses periodically for obstacle detection and to deduce from the transit time the position of obstacles, whereby in the evaluation over time correlated lasting echoes are amplified over several measuring cycles, while uncorrelated lasting echoes are suppressed.

From the DE 10 2012 015 967 A1 a method is known for decoding a receive signal received from an ultrasonic sensor of a motor vehicle, in which a transmit signal of the ultrasonic sensor is transmitted coded and for decoding the receive signal is correlated with a reference signal, wherein prior to correlating the receive signal with the reference signal, a frequency shift of the receive signal relative to the Transmitting signal is determined and the received signal is correlated with the shifted by the determined frequency shift in its transmission signal as a reference signal, wherein for determining the frequency shift of the received signal selbiges received signal is subjected to a Fourier transform and the frequency shift is determined based on a result of the Fourier transform.

From the DE 10 2011 085 286 A1 is a method for detecting the environment of a vehicle by means of ultrasound, wherein ultrasound pulses are emitted and the reflected ultrasound echoes are detected on objects, characterized in that the detection area is divided into at least two distance ranges, wherein the ultrasonic pulses used for the detection in the respective distance range emitted independently and are coded by different frequencies.

From the WO 2014 108 300 A1 Device and a method for environmental sensors by means of a signal converter and an evaluation are known, are filtered from the environment received signals with a first impulse response length at a first time during a measurement cycle and with a second longer impulse response length at a second later time within the same measurement cycle signals time-dependent ,

From the DE 10 2015 104 934 A1 A method is known for providing information dependent on an object detected in a surrounding area of a motor vehicle DE 10 2015 104 934 A1 the surrounding area of the motor vehicle is detected with a sensor device of the motor vehicle and information is provided at a communication interface in the motor vehicle. In this case, sensor raw data are stored in a sensor device-side control unit as information about a free space detected between the sensor device and an object detected in the surrounding area. These sensor raw data are in accordance with the technical teaching of DE 10 2015 104 934 A connected to a communication interface connected to the sensor device-side control unit for transmission to and for further processing with a further control unit of a processing device comprising the two control units and designed to create a surrounding area map.

The technical teachings of the above rights are all guided by the idea to perform the detection of an object in front of the vehicle with the help of the ultrasonic sensor already in the ultrasonic sensor and only then to transmit the object data after detection of the objects. However, this synergy effects are lost when using multiple ultrasonic transmitter.

From the DE 10 2010 041 424 A1 a method is known for detecting an environment of a vehicle with a number of sensors, in which at least one sensor detects at least one echo cycle during at least one echo cycle and is compressed with an algorithm, and in which the at least one compressed one Echo information is transmitted to at least one processing unit. Although the focus DE 10 2010 041424 A1 even on the compressed transmission of detected object data, but it is already recognized that it makes sense in general to transmit data extracted from the received echo signal (echo information) compressed to the controller without having to specify a compression method becomes.

From the DE 10 2013 226 373 A1 a method for sensor connection is known. In section [0006] of DE 10 2013 226 373 A1 explain the authors of the DE 10 2013 226 373 A1 the state of the art. In claim 1 of DE 10 2013 226 373 A1 claim the authors of DE 10 2013 226 373 A1 this self-mentioned prior art.

From the US 2006/0 250 297 A1 a system for sensor fusion is known.

task

The invention is therefore based on the object to provide a solution which solves the above object of reducing the need for bus bandwidth for the transmission of measurement data from the ultrasonic sensor system to the computer system and optionally has further advantages.

This object is achieved by a method according to claim 1 and a sensor system according to claim 32.

solution

As explained above, the technical teachings of the prior art are all guided by the idea of performing the detection of an object in front of the vehicle with the aid of the ultrasound sensor already in the ultrasound sensor and then only to transmit the object data after recognition of the objects. However, since synergy effects are lost in the use of multiple ultrasound transmitters, it was recognized during the preparation of the disclosure presented here that it is not sensible to transmit only the echo data of the ultrasound sensor itself, but all the data and only in a central computer system, the data to evaluate several sensors. For this purpose, the compression of the data for transmission over a data bus with a lower bus bandwidth but must be done differently than in the prior art. As a result, then synergy effects can be developed. For example, it is conceivable that a vehicle has more than one ultrasonic sensor. In order to be able to differentiate between the two sensors, it makes sense to send these two sensors with different coding. In contrast to the prior art, however, both sensors should now detect the ultrasound echoes of both emissions of both ultrasound sensors and transmit them suitably compressed to the central computer system, where the ultrasound reception signals are reconstructed. Only after the reconstruction (decompression) the recognition of the objects takes place. This also allows the fusion of ultrasound sensor data with other sensor systems such as radar etc.

A method is proposed for transmitting sensor data from a sensor to a computer system. Particularly suitable is the method for use for transmitting data of an ultrasonic signal received from an ultrasonic sensor to a control unit as a computer system in a vehicle. The procedure is based on the 1 explained. According to the proposed method, an ultrasonic burst is first generated and emitted into a free space, typically in the environment of the vehicle (step α of the 1 ). An ultrasonic burst consists of this several ultrasound frequency successive sound pulses. This ultrasonic burst arises because a mechanical oscillator in an ultrasound transmitter or ultrasound transducer slowly starts to oscillate and oscillates again. The ultrasound burst thus emitted by the exemplary ultrasound transducer is then reflected on objects in the vicinity of the vehicle and received by an ultrasound receiver or the ultrasound transducer itself as an ultrasound signal and converted into an electrical reception signal (step β of the 1 ). The ultrasound transmitter is particularly preferably identical to the ultrasound receiver and will be referred to below as a transducer. However, the principle explained below can also be applied to separate receivers and transmitters. In the proposed ultrasonic sensor is a signal processing unit, which now analyzes the received electrical received signal and compressed (step y of the 1 ) to minimize the necessary data transmission and to provide clearance for the said status messages and other control commands of the control computer to the signal processing unit or the ultrasonic sensor system. Subsequently, the compressed electrical received signal is transmitted to the computer system (step δ of the 1 ).

The associated method thus serves to transmit sensor data, in particular an ultrasonic sensor, from a sensor to a computer system, in particular in a vehicle. It starts by sending out an ultrasonic burst (step α of the 1 ). This is followed by receiving an ultrasonic signal and forming an electrical received signal (step β of the 1 ) and performing data compression of the received signal (step y of the 1 ) for generating compressed data (step y of the 1 ) and detecting at least two or three or more predetermined characteristics. Preferably, the electrical received signal is sampled (step ya of the 2 ) is converted into a sampled receive signal consisting of a time discrete stream of samples. Each sample can typically be assigned a sampling time as the time stamp of this sample. The compression can be achieved, for example, by a wavelet transformation (step yb of the 2 ) respectively. For this purpose, the received ultrasonic signal in the form of the sampled received signal with predetermined basic signal forms, which are stored for example in a library, by forming a correlation integral (see also Wikipedia for this term) between the predetermined signal fundamental forms and the sampled received signal to be compared. The predefined signal basic forms are also referred to below as signal object classes. By forming the correlation integral, respective spectral values of this prototypical signal object class are determined for each of these prototypical signal object classes. As this happens continuously, the spectral values themselves represent a stream of time-discrete instantaneous spectral values, with each spectral value again being able to be assigned a timestamp. An alternative but mathematically equivalent method is the use of matched filters in each predetermined signal object class (basic signal form). As a rule, several prototypical signal object classes are used, which can also be subjected to different time spreads (see also "wavelet analysis"), typically results in a time-discrete stream of multidimensional vectors of spectral values of different prototypical signal object classes and their different respective temporal spreads. Whereby each of these multidimensional vectors is again assigned a time stamp. Each of these multidimensional vectors is a so-called feature vector. It is thus a time discrete stream of feature vectors. Each of these feature vectors is preferably assigned a timestamp again. (Step yb of the 2 )

Due to the continuous time shift thus also results in a temporal dimension. As a result, the feature vector of the spectral values can also be supplemented by values of the past or values which depend on these, for example time integrals or derivatives or filter values of one or more of these values, etc. This can further increase the dimensionality of these feature vectors within the feature vector data stream. In order to keep the effort small in the following, therefore, the restriction to a few prototypical signal object classes during the extraction of the feature vectors from the sampled input signal of the ultrasonic sensor makes sense. Thus, for example, matched filters can then be used to continuously monitor the occurrence of these prototypical signal object classes in the received signal.

As particularly simple prototypical signal object classes, for example, the isosceles triangle and the double point can be specially named here. As a rule, a prototypical signal object class consists of a given spectral coefficient vector, that is to say a predetermined prototype feature vector value.

For determining the relevance of the spectral coefficients of a feature vector of an ultrasound echo signal, the determination of the magnitude of a spacing of these properties, the elements of the vector of the momentary spectral coefficients (feature vector), is at least one prototypical combination of these properties ( Prototype) in the form of a prototypical signal object class which is symbolized by a given prototype feature vector (prototype or prototype vector) from a library of predetermined prototypical signal object class vectors (step yd of the 2 ). Preferably, the spectral coefficients of the feature vector are normalized before correlation with the prototypes (step yc of the 2 ). The distance determined in this distance determination can consist, for example, of the sum of all differences between in each case one spectral coefficient of the given prototype feature vector (prototype or prototype vector) of the respective prototype and the corresponding normalized spectral coefficient of the current feature vector of the ultrasound echo signal. An Euclidean distance would be formed by the root of the sum of the squares of all differences between one spectral coefficient of the given prototype feature vector (prototype or prototype vector) of the prototype and the corresponding normalized spectral coefficient of the current feature vector of the ultrasound echo signal. However, this distance formation is usually too expensive. Other methods of spacing are conceivable. Each predefined prototype feature vector (prototype or prototype vector) can then be assigned a symbol and optionally also a parameter, eg the distance value and / or the amplitude before normalization. If the distance determined in this way falls below a first threshold value and if it is the smallest distance of the current feature-vector value to one of the predetermined prototypical feature vector values (prototypes or values of the prototype vectors), then its symbol is used further as a recognized prototype. This results in a pairing of recognized prototypes and timestamps of the current feature vector. It is then preferable to transfer the data (step δ of the 2 ), here the detected symbol, which best symbolizes the recognized prototype, and for example the distance and the time of occurrence (time stamp) to the computer system only if the amount of this distance is below the first threshold and the detected prototype to be transmitted Prototype is. It may in fact be the case that unrecognizable prototypes are also stored, for example for noise, ie, for example, the absence of reflections, etc. These data are irrelevant for the obstacle detection and should therefore possibly not be transmitted. A prototype is thus recognized if the amount of the determined distance between the current feature vector value and the given prototype feature vector value (prototype or value of the prototype vector) is below this first threshold value (step ye of FIG 2 ). It is therefore no longer transmit the ultrasonic echo signal itself, but only a sequence of symbols for recognized typical temporal signal waveforms and time stamps associated with these waveforms in a certain period of time (step δ of the 2 ). It is then preferred for each detected signal object only one symbol for the detected waveform prototype whose parameters (eg amplitude of the envelope and / or temporal extension) and a temporal reference point of the occurrence of this waveform prototype (the time stamp) transmitted as recognized signal object. The transmission of the individual samples or times at which thresholds are exceeded by the envelope of the sampled received signal, etc. is eliminated. In this way, this selection of the relevant prototypes leads to massive data compression and to a reduction of the required bus bandwidth.

Thus, there is a quantitative detection of the presence of a combination of properties forming an estimate - here e.g. the inverse distance between the representative of the prototypical signal object class in the form of the given prototype feature vector (prototype or prototype vector) and the subsequent transfer of the compressed data to the computer system if the amount of this estimate (eg inverse distance) is above a second threshold or the inverse estimate is below a first threshold. The signal processing unit of the ultrasonic sensor thus performs data compression of the received signal to generate compressed data. The ultrasonic sensor then transmits the data thus compressed, preferably only the codes (symbols) of the prototypes thus recognized, their amplitude and / or temporal extension and the time of occurrence (time stamp), to the computer system. As a result, the EMC burden is minimized by the data transmission via the data bus between the ultrasonic sensor and the computer system and it can be transmitted status data of the ultrasonic sensor for system error detection in the time intervals to the computer system via the data bus between the ultrasonic sensor and the computer system, which improves the latency. When working out the proposal, it was recognized that the transfer of data over the data bus must be prioritized. Messages safety-critical errors of the sensor, so here example of the ultrasonic sensor to the computer system have the highest priority, since they affect the validity of the measurement data of the ultrasonic sensor with high probability. This data is sent from the sensor to the computer system. The second-highest priority are requests from the computer system for carrying out safety-relevant self-tests. Such commands are sent from the computer system to the sensor. The third highest priority is the data of the ultrasonic sensor itself, since the latency must not be increased. All other data has lower priority for transmission over the data bus.

It is particularly advantageous if the method for transmitting sensor data, in particular an ultrasonic sensor, from a sensor to a computer system, in particular in a vehicle, comprises transmitting an ultrasonic burst with a start ( 57 ) and end ( 56 ) of transmitting the ultrasonic burst and comprising receiving an ultrasonic signal and forming a received signal for a reception time ( T _E ) at least from the end ( 56 ) of transmitting the ultrasonic burst and comprising transmitting the compressed data via a data bus, in particular a single-wire data bus, to the computer system in such a way that the transmission ( 54 ) of the data from the sensor to the computer system with a start command ( 53 ) from the computer system to the ultrasonic sensor via the data bus and before the end ( 56 ) of the transmission of the ultrasonic burst begins or after a start command ( 53 ) from the computer system to the sensor via the data bus and before the start ( 57 ) of transmitting the ultrasonic burst begins. The transfer ( 54 ) then takes place after the start command ( 53 ) periodically until an end of the data transmission ( 58 ). This end of the data transfer ( 58 ) is then after the end of the reception time ( T _E ).

A further variant of the proposed method thus provides, as a first step of the data compression, the formation of a feature vector signal (stream of feature vectors with n feature vector values and n as dimension of the feature vector) from the received signal. Such a feature vector signal may include a plurality of analog and digital data signals. It thus represents a chronological sequence of more or less complex data / signal structures. In the simplest case, it can be understood as a vectorial signal consisting of several sub-signals.

For example, it may be useful to form a first and / or higher temporal derivative of the received signal or the single or multiple integral of the received signal, which are then sub-signals within the feature vector signal.

An envelope signal of the received signal may also be formed, which is then a sub-signal within the feature vector signal.

Furthermore, it may be useful to fold the received signal with the emitted ultrasonic signal and thus form a correlation signal, which may then be a partial signal within the feature vector signal. In this case, on the one hand, the signal can be used as a transmitted ultrasonic signal, which was used to drive the driver for the transmitter, or, for example, a signal that was measured at the transmitter and thus better corresponds to the actual radiated sound wave.

Finally, it may be useful to use optimally matched filters to detect the occurrence of predetermined signal objects and to form an optimum filter signal for the respective signal object of some of the predetermined signal objects. A matched filter is a filter that optimizes the signal-to-noise ratio (SNR). In the disturbed ultrasonic signal received the predefined signal objects are to be detected. In the literature one often finds the terms correlation filter, signal-matched filter (SAF) or only matched filter. The optimal filter serves to optimally determine the presence (detection) of the amplitude and / or the position of a known signal form, the predetermined signal object, in the presence of disturbances (parameter estimation). These disturbances can be, for example, signals from other ultrasound transmitters and / or ground echoes.

The optimum filter output signals are then preferably partial signals within the feature vector signal.

Certain events may be signaled in separate sub-signals of the feature vector signal. These events are signal primitives in the sense of this disclosure. Signal fundamental objects thus do not include signal forms, such as recheck pulses or wavelets or wave trains, but prominent points in the course of the received signal and / or in the course of signals derived therefrom, such as an envelope signal, which can be obtained, for example, by filtering from the received signal.

For example, another signal, which may be a sub-signal of the feature vector signal, may detect whether the envelope of the received signal, the envelope signal, crosses a predetermined third threshold. It is therefore a signal that signals the presence of a signal basic object within the received signal and thus the feature vector signal.

Another signal, which may be a sub-signal of the feature vector signal, may be For example, detect whether the envelope of the received signal, the envelope signal, a predetermined fourth threshold, which may be identical to the third threshold value ascending crosses. It is therefore a signal that signals the presence of a signal basic object within the received signal and thus the feature vector signal.

Another signal, which may be a sub-signal of the feature vector signal, may detect, for example, whether the envelope of the received signal, the envelope signal, crosses a predetermined fifth threshold, which may be identical to the third or fourth threshold. It is therefore a signal that signals the presence of a signal basic object within the received signal and thus the feature vector signal.

For example, another signal, which may be a component signal of the feature vector signal, may detect whether the envelope of the received signal, the envelope signal, has a maximum above a sixth threshold, which may be identical to the aforementioned third to fifth thresholds. It is therefore a signal that signals the presence of a signal basic object within the received signal and thus the feature vector signal.

For example, another signal, which may be a component signal of the feature vector signal, may detect whether the envelope of the received signal, the envelope signal, is a minimum above a seventh threshold, which may be identical to the aforementioned third through sixth thresholds. It is therefore a signal that signals the presence of a signal basic object within the received signal and thus the feature vector signal.

In this case, it is preferably evaluated whether the at least one preceding maximum of the envelope has a minimum distance to the minimum in order to avoid detection of noise. Other filters are conceivable at this point. It can also be checked whether the time interval between this minimum and a preceding maximum is greater than a first time minimum distance. The fulfillment of these conditions sets in each case a flag or signal which itself is preferably a partial signal of the feature vector signal.

Likewise, it should be checked in an analogous manner whether the temporal and amplitude-related distances of the other signal objects satisfy certain plausibility requirements, such as temporal minimum distances and / or minimum distances in the amplitude. From these tests, further, even analog, binary or digital sub-signals can be derived, which thus further increase the feature vector signal in its dimensionality.

Possibly. For example, in a significance enhancement stage, the feature vector signal may be translated to a significant feature vector signal, e.g. be transformed by a linear mapping or a matrix polynomial of higher order. In practice, however, it has been shown that this is not necessary, at least for today's requirements.

According to the proposed method, recognizing and classifying signal objects into detected signal object classes within the received signal is based on the feature vector signal or the significant feature vector signal.

If, for example, the amplitude of the output signal of an optimum filter, and thus of a partial signal of the feature vector signal above an optionally optimal filter-specific eighth threshold value, the signal object, for the detection of which the optimal filter is designed, can be regarded as detected. In this case, other parameters are preferably taken into account. For example, if an ultrasonic burst of increasing frequency was sent during the burst (called chirp-up), then an echo is expected to have this modulation property. If the waveform of the envelope, for example a triangular waveform of the envelope, coincides temporally locally with an expected waveform, but does not match the modulation characteristic, then it is not an echo of the transmitter but a jamming signal that may result from other ultrasound transmitters or from overreach. In this respect, the system can then distinguish between self-echoes and foreign echoes, whereby one and the same signal form is assigned to two different signal objects, namely self-echoes and foreign echoes. The transmission of the internal echoes on the Dtanebus from the sensor to the computer system is preferably prioritized over the transmission of foreign echoes, since the former are usually security-relevant and second are usually not security relevant.

Typically, at least one associated signal object parameter is assigned to each recognized signal object or determined for this signal object. This is preferably a timestamp indicating when the object was received. In this case, the time stamp may relate, for example, to the start of the time of the signal object in the received signal or the end of the time or the temporal position of the temporal center of gravity of the signal object etc. Also, other signal object parameters, such as amplitude, extension, etc. are conceivable. In one variant of the proposed method, at least one of the assigned signal object parameters is thus transmitted with a symbol for the at least one recognized signal object class. The signal object parameter is preferably a time value as a Zetstempel and indicates a temporal position, which is suitable to be able to conclude from the time since the transmission of a previous ultrasonic burst. The determination of a determined distance of an object as a function of a time value thus determined and transmitted is preferably carried out later.

Finally, the prioritized transmission of the recognized signal object classes in the form of associated symbols with time stamps preferably follows together with the associated signal object parameters. The transmission can also be done in more complex data structures (English: Records). For example, it is conceivable first to transmit the times of the detected safety-relevant signal objects (eg identified obstacles) and then to transmit the recognized signal object classes of the safety-relevant signal objects. This further reduces the latency.

The proposed method comprises, in at least one variant, the determination of a chirp value as associated signal object parameter, which indicates whether the detected signal object is an echo of an ultrasound transmit burst with chirp-up or a chirp-down or a no-signal. Chirp properties. Chirp-Up means that the frequency within the received signal object increases in the received signal. Chirp down means that the frequency within the received signal object drops in the received signal. No-chirp means that the frequency within the received signal object in the received signal remains substantially the same. At this point I would like to refer to the still unpublished German patent applications DE 10 2017 100 837.3 and DE 10 2017 100 835.7 which are the fullest part of this disclosure.

Thus, in a variant of the method, a confidence signal is also obtained by forming the correlation, e.g. by forming a time-continuous or time-discrete correlation integral between the received signal or instead of the received signal with a signal derived from the received signal on the one hand and a reference signal, for example the ultrasonic transmitting signal or another expected wavelet, on the other hand. The confidence signal is then typically a sub-signal of the feature vector signal, ie, a component of the feature vector consisting of a sequence of vectorial samples (feature vector values).

In a variant of the method, a phase signal is also formed on this basis which indicates the phase shift of, for example, the received signal or a signal formed therefrom (for example the confidence signal) relative to a reference signal, for example the ultrasound transmit signal and / or another reference signal. The phase signal is then typically also a sub-signal of the feature vector signal, ie a component of the feature vector, which consists of a sequence of vectorial samples.

Similarly, in a further variant of the proposed method, a phase confidence signal can be formed by forming the correlation between the phase signal or a signal derived therefrom on the one hand and a reference signal and used as a partial signal of the feature vector signal. The phase confidence signal is then typically also a sub-signal of the feature vector signal, ie a component of the feature vector, which consists of a sequence of vectorial samples.

When evaluating the feature vector signal, it then makes sense to perform a comparison of the phase confidence signal with one or more threshold values for generating a discretized phase confidence signal, which itself becomes a partial signal of the feature vector signal can.

In one variant of the proposed method, the evaluation of the feature vector signal and / or of the significant feature vector signal may be carried out such that one or more distance values are formed between the feature vector signal and one or more signal object prototype values for recognizable signal object classes , Such a distance value may be Boolean, binary, discrete, digital or analog. Preferably, all distance values are linked together in a nonlinear function. Thus, in an expected triangular chirp-up echo, a received chirp-down echo may be discarded in triangular form. For the purposes of this disclosure, this discarding is a non-linear process.

Conversely, the triangle can be different in the received signal. This applies first of all to the amplitude of the triangle in the received signal. If the amplitude in the received signal is sufficient, for example, the optimum filter assigned to this triangular signal supplies a signal above a predetermined ninth threshold value. In that case, for example, this signal object class (triangular signal) can then be assigned a detected signal object at this time of the crossing. In that case, the distance value between the feature vector signal and the prototype (here the ninth threshold value) falls below one or more predetermined binary, digital or analog distance values (here 0 = intersection).

In a further variant of the method, at least one signal object class is wavelets which are estimated by estimation devices (eg optimal filters) and / or estimation methods (eg estimation programs that run in a digital signal processor) and thus detected. The term wavelet refers to functions that are continuous or discrete wavelet transformation. The word "wavelet" is a re-creation from the French "ondelette", which means "small wave" and partly verbally ("onde" → "wave"), partly phonetically ("-lette" → "-let") into English has been. The term "wavelet" was coined in the 1980s in geophysics (Jean Morlet, Alex Grossman) for functions that generalize the short-term Fourier transform, but is used since the late 1980s, only in the meanings of today. In the 1990s, a veritable wavelet boom arose, triggered by the discovery of compact, continuous (to any order of differentiability) and orthogonal wavelets by Ingrid Daubechies (1988) and the development of the algorithm of fast wavelet transformation (FWT) using multi-scale analysis (MRA) by Stephane Mallat and Yves Meyer (1989).

In contrast to the sine and cosine functions of the Fourier transformation, the most commonly used wavelets not only have locality in the frequency spectrum, but also in the time domain. Here, "locality" is to be understood in the sense of small dispersion. The probability density is the normalized absolute square of the considered function or of its Fourier transform. The product of both variances is always larger than a constant, analogous to the Heisenberg uncertainty principle. Out of this limitation, Paley-Wiener theory (Raymond Paley, Norbert Wiener), a precursor to the discrete wavelet transform, emerged in functional analysis, and the Calderon-Zygmund theory (Alberto Calderon, Antoni Zygmund), that of continuous wavelet theory. Transformation corresponds.

Although the integral of a wavelet function is always 0 in professional use, the wavelet function generally takes the form of outgoing (decreasing) waves (that is, "corrugations" = ondelets = wavelets). For the purpose of this disclosure, however, wavelets are also to be allowed which have an integral other than 0. Here, by way of example, the rectangle and triangular wavelets described below are mentioned. This further interpretation of the term "wavelet" is common in American-speaking countries and therefore well-known. This further interpretation should also apply here.

Important examples of 0-integral wavelets are the Haar wavelet (Alfred Haar 1909), the Daubechies wavelets (around 1990) named after Ingrid Daubechies, the Coiflet wavelets also constructed by them, and the rather theoretically significant Meyer wavelet (Yves Meyer, around 1988).

Wavelets are available for spaces of any dimension, usually a tensor product of a one-dimensional wavelet basis is used. Due to the fractal nature of the two-scale equation in the MRA, most wavelets have a complicated shape, most of them have no closed shape. This is of particular importance because the aforementioned feature vector signal is multi-dimensional and thus allows the use of multi-dimensional wavelets for signal object detection.

A particular variant of the proposed method is therefore the use of multidimensional wavelets with more than two dimensions for signal object recognition. In particular, the use of corresponding optimal filters for the detection of such wavelets with more than two dimensions is proposed in order to supplement the feature vector signal by further partial signals suitable for detection.

A particularly suitable wavelet is, for example, a triangular wavelet. This is characterized by a start time of the triangular wavelet, a temporally substantially following the start time of the triangular wavelet, temporally substantially linear increase in the wavelet amplitude up to a maximum of the amplitude of the triangular wavelet and the maximum of the triangular wavelet and a temporally subsequent, temporally substantially linear decrease of the wavelet amplitude up to an end of the triangular wavelet.

Another particularly suitable wavelet is a rectangular wavelet, which also includes trapezoidal wavelets within the meaning of this disclosure. A rectangular wavelet is characterized by a start time of the rectangular wavelet, which is followed by an increase of the wavelet amplitude of the rectangular wavelet with a first temporal steepness of the rectangular wavelet up to a first plateau time of the rectangular wavelet. The first plateau time of the rectangular wavelet is followed by a persistence of the wavelet amplitude with a second steepness of the wavelet amplitude up to a second plateau time of the rectangular wavelet. The second plateau time of the rectangular wavelet is followed by a fall with a third temporal slope until the temporal end of the rectangular wavelet. The amount of the second temporal slope is less than 10% of the amount of the first temporal slope and less than 10% of the amount of the third temporal slope.

Instead of the previously described wavelets, it is also possible to use other two-dimensional wavelets, such as a sine half-wave wavelet, for example, which also has an integral other than 0.

It is proposed that, when using wavelets, the time shift of the respective wavelet of the detected signal object is used as a signal object parameter. For example, this shift can be determined by correlation. It is further proposed that, when using wavelets, the time of exceeding the level of the output of an optimum filter suitable for detecting the relevant wavelet over a predefined tenth threshold value is preferably used for this signal object or wavelet becomes. Preferably, the envelope of the received signal and / or a phase signal and / or a confidence signal, etc. is evaluated.

Another possible signal object parameter that can be detected is a temporal compression or stretching of the respective wavelet of the detected signal object. Likewise, an amplitude of the wavelet of the detected signal object can be determined.

It was recognized in the preparation of the proposal for the method disclosed here that it is advantageous to first transfer the data of the detected signal objects of the very quickly arriving echoes from the sensor to the computer system and then only the subsequent data of the later recognized signal objects. Preferably, at least the recognized signal object class and a time stamp are always transmitted, which should preferably indicate when the signal object has arrived at the sensor again. As part of the recognition process, scores can be assigned to the various signal objects which are suitable for a section of the received signal which indicate which probability is assigned to the present of this signal object in accordance with the used estimation algorithm. Such a score is binary in the simplest case. However, it is preferably a complex, real or integer number. It may be, for example, the determined distance. If several signal objects have a high score value, it may be useful in some cases to transfer the data of detected signal objects with lower score values. In order to allow the computer system to handle correctly, not only the date (symbol) of the detected signal object and the time stamp for the respective signal object should be transmitted for this case, but also the determined score value. Instead of transmitting only the date (symbol) of the detected signal object and the time stamp for the signal object corresponding to this symbol, the date (symbol) of the signal object with the second smallest distance and its time stamp can also be transmitted for the signal object corresponding to this second most probable symbol. Thus, in this case, a hypothesis list of two recognized signal objects and their temporal positions as well as additionally assigned score values are transmitted to the computer system. Of course, the transmission of a list of hypotheses consisting of more than two symbols for more than two recognized signal objects and their temporal positions and additionally assigned score values to the computer system done.

Preferably, the transmission of the data of the detected signal object class and the associated data such as time stamp and score values of the respective detected signal object classes, ie the associated signal object parameters, according to the FIFO principle. This ensures that always the data of the reflections of the closest objects are transmitted first and thus the safety-critical case of the collision of the vehicle with an obstacle is processed prioritized according to probability.

In addition to the transmission of measured data, the transmission of error states of the sensor can also take place. This can also be done during a reception time ( T _E ) occur when the sensor detects through self-test devices that there is a defect and the previously transmitted data could potentially be faulty. This ensures that the computer system can gain knowledge of a change in the evaluation of the measurement data at the earliest possible time and can discard it or treat it differently. This is of particular importance for emergency braking systems, since an emergency braking is a safety-critical intervention that may only be initiated if the underlying data have a corresponding confidence value. On the other hand, therefore, the transmission of the measured data, that is to say, for example, the date of the recognized signal object class and / or the transmission of the one associated signal object parameter is postponed and thus prioritized lower. Of course, termination of the transmission is possible if an error occurs in the sensor. In some cases, it may happen that an error seems possible, but not sure. In this respect, the continuation of a transmission may be indicated in such cases. The transmission of safety-critical errors of the sensor is thus preferably prioritized higher.

In addition to the previously described wavelets having an integration value of 0 and the signal sections additionally denoted here as wavelets with an integration value different from 0, certain points in the course of the received signal can be regarded as basic signal objects in the sense of this disclosure, which can be used for data compression and instead of samples of the received signal can be transmitted. This subset in the set Possible signal basic objects are referred to below as signal times. The signal times are therefore in the sense of this disclosure a special form of the basic signal objects.

A first possible signal time and thus a basic signal object is a crossing of the amplitude of the envelope signal ( 1 ) with the amplitude of an eleventh threshold signal ( SW ) in ascending direction.

A second possible signal time and thus a basic signal object is a crossing of the amplitude of the envelope signal ( 1 ) with the amplitude of a twelfth threshold signal ( SW ) in descending direction.

A third possible signal time and thus a basic signal object is a maximum of the amplitude of the envelope signal ( 1 ) above the amplitude of a thirteenth threshold signal ( SW ).

A fourth possible signal time and thus a basic signal object is a minimum of the amplitude of the envelope signal ( 1 ) above the amplitude of a fourteenth threshold signal ( SW ).

Possibly. it may be useful for these four exemplary types of signal timing and other types of signal timing signal-type specific threshold signals ( SW ) to use.

1. 1. das Auftreten eines ersten möglichen Signalzeitpunkts mit einem Kreuzen der Amplitude des Hüllkurvensignals (1) mit der Amplitude eines Schwellwertsignals (SW) in aufsteigender Richtung und daran zeitlich anschließend
2. 2. das Auftreten eines dritten möglichen Signalzeitpunkts mit einem Maximum der Amplitude des Hüllkurvensignals (1) oberhalb der Amplitude eines Schwellwertsignals (SW) und daran zeitlich anschließend
3. 3. das Auftreten eines zweiten möglichen Signalzeitpunkts mit einem Kreuzen der Amplitude des Hüllkurvensignals (1) mit der Amplitude eines Schwellwertsignals (SW) in absteigender Richtung

in zeitlicher Korrelation zum Überschreiten des besagten Mindestpegels am Ausgang des besagten Optimal-Filters erwartet werden. Das beispielhafte Signalobjekt eines Dreiecks-Wavelets besteht in diesem Beispiel also in der vordefinierten Abfolge dreier Signalgrundobjekte, die erkannt, durch ein Symbol ersetzt wird und als dieses Symbol bevorzugt zusammen mit seinem Auftretenszeitpunkt, dem Zeitstempel, übertragen wird. Dieses Überschreiten des besagten Mindestpegels am Ausgang des besagten Optimal-Filters ist übrigens ein weiteres Beispiel für einen fünften möglichen Signalzeitpunkt und damit ein weiteres mögliches Signalgrundobjekt.The temporal sequence of signal basic objects is typically not arbitrary. This is exploited in this disclosure, since it is preferable not to transmit the basic signal objects, which are of a simpler nature, but to recognize patterns of sequences of these basic signal objects, which then represent the actual signal objects. For example, if a triangle wavelet is included in the envelope signal ( 1 ) of sufficient amplitude, then, in addition to a corresponding minimum level at the output of an optimum filter suitable for the detection of such a triangular wavelet

1. 1. the occurrence of a first possible signal time with a crossing of the amplitude of the envelope signal ( 1 ) with the amplitude of a threshold signal ( SW ) in ascending direction and afterwards
2. 2. the occurrence of a third possible signal time with a maximum of the amplitude of the envelope signal ( 1 ) above the amplitude of a threshold signal ( SW ) and afterwards
3. 3. the occurrence of a second possible signal time with a crossing of the amplitude of the envelope signal ( 1 ) with the amplitude of a threshold signal ( SW ) in descending direction

can be expected in time correlation to exceed the said minimum level at the output of said optimal filter. The exemplary signal object of a triangular wavelet thus consists in this example in the predefined sequence of three basic signal objects, which is recognized, replaced by a symbol and preferably transmitted as this symbol together with its time of occurrence, the time stamp. Incidentally, this exceeding of the said minimum level at the output of said optimum filter is a further example of a fifth possible signal time and thus another possible basic signal object.

The resulting grouping and temporal sequence of detected signal fundamental objects can themselves, for example by a Viterbi decoder, be recognized as a predefined, expected grouping or temporal sequence of signal basic objects and can thus again represent a basic signal object. Thus, a sixth possible signal time and thus a basic signal object is the occurrence of such a predefined grouping and / or time sequence of other basic signal objects.

If such a grouping of basic signal objects or chronological sequence of such signal object classes in the form of a signal object is detected, then the transmission of the symbol of this recognized summary signal object class and at least one associated signal object parameter preferably follows instead of the transmission of the individual signal basic objects, as this saves considerable data bus capacity. However, there may be cases where both are transmitted. In this case, the date (symbol) of the signal object class of a signal object is transmitted, which is a predefined time sequence and / or grouping of other signal basic objects. In order to achieve compression, it is advantageous if at least one signal object class (symbol) of at least one of these other signal basic objects is not transmitted.

A temporal grouping of signal basic objects is present in particular when the time interval of these signal basic objects does not exceed a predefined distance. In the example mentioned above, the duration of the signal in the optimal filter should be considered. Typically, the optimal filter should be slower than the comparators. Therefore, the change in the output signal of the optimum filter should be in a fixed temporal relationship to the time occurrence of the relevant signal times.

So here's a method for transmitting sensor data, in particular an ultrasonic sensor, from a sensor to a Computer system, in particular in a vehicle, proposed, which begins with the emission of an ultrasonic burst and the receiving of an ultrasonic signal and the formation of a discrete-time received signal consisting of a sequence of samples. Each sample is assigned a time date (time stamp). This is followed by the determination of at least two parameter signals in each case concerning the presence of a respective signal basic object assigned to the respective parameter signal with the aid of at least one suitable filter (eg an optimum filter) from the sequence of sample values of the received signal. The resulting parameter signals (feature vector signals) are likewise embodied as a time-discrete sequence of respective parameter signal values (feature vector values) which are each correlated with a datum (time stamp). Thus, each parameter signal value (feature vector value) is assigned with exactly one temporal date (time stamp). These parameter signals together are referred to below as a feature vector signal. The feature vector signal is thus designed as a time-discrete sequence of feature vector signal values with n parameter signal values in each case, which consist of the parameter signal values and further parameter signal values with the same respective temporal date (time stamp). Here, n is the dimensionality of the individual feature vector signal values, which are preferably the same from one feature vector value to the next feature vector value. Each feature vector signal value thus formed is assigned this respective temporal date (time stamp). This is followed by the evaluation of the time profile of the feature vector signal in the resulting n-dimensional phase space as well as the closing on a detected signal object with determination of an evaluation value (eg the distance). As explained above, a signal object consists of a chronological sequence of signal basic objects. The signal object is typically assigned a predefined symbol. Figuratively speaking, it is checked here whether the point pointed to by the n-dimensional feature vector signal in the n-dimensional phase space passes through the n-dimensional phase space in a predetermined time sequence at predetermined points in this n-dimensional phase space closer than a given maximum distance approaches. The feature vector signal thus has a time course. An evaluation value (eg a distance) is then calculated which can, for example, reflect the probability of the existence of a specific sequence. The comparison of this evaluation value, which is again associated with a time date (time stamp), then takes place with a threshold value vector to form a Boolean result which can have a first and a second value. If this Boolean result has the first value for this time data (time stamp), the symbol of the signal object and the time associated with this symbol (time stamp) are transmitted from the sensor to the computer system. Possibly. Depending on the detected signal object, further parameters can be transmitted.

Particularly preferably, the data transmission takes place in the vehicle via a serial bidirectional single-wire data bus. The electrical return is hereby preferably ensured by the body of the vehicle. The sensor data are preferably sent to the computer system in a power-modulated manner. The data for controlling the sensor are preferably transmitted to the sensor in a voltage-modulated manner by the computer system. According to the invention, it has been recognized that the use of a PSI5 data bus and / or a DSI3 data bus is particularly suitable for data transmission. Furthermore, it was recognized that it is particularly advantageous to carry out the transmission of the data to the computer system with a transmission rate of> 200 kbit / s and from the computer system to the at least one sensor with a transmission rate> 10 kbit / s, preferably 20 kbit / s , Furthermore, it has been recognized that the transmission of data from the sensor to the computer system should be modulated with a transmit current to the data bus whose current should be less than 50 mA, preferably less than 5 mA, preferably less than 2.5mA. For these operating values, these buses must be adapted accordingly. The basic principle remains.

• • Optimalfilter,
• • Komparatoren,
• • Schwellwertsignalerzeugungsvorrichtungen zur Erzeugung eines oder mehrerer Schwellwertsignale (SW),
• • Differenzierer zur Bildung von Ableitungen,
• • Integrierer zur Bildung integrierter Signale,
• • sonstige Filter,
• • Hüllkurvenformer zur Erzeugung eines Hüllkurvensignals aus dem Empfangssignal,
• • Korrelationsfilter zum Vergleich des Empfangssignals oder von daraus abgeleiteten Signalen mit Referenzsignalen.

To carry out the above-described methods, a computer system having a data interface to said data bus, preferably said single-wire data bus, is required to support the decompression of the data thus compressed. In general, however, the computer system will not perform a complete decompression, but, for example, evaluate only the time stamp and the recognized signal object type. The sensor required for carrying out one of the methods described above has at least one transmitter and at least one receiver for generating a received signal, which may also be combined as one or more transducers. Furthermore, it has at least devices for processing and compression of the received signal and a data interface for transmitting the data via the data bus, preferably the said single-wire data bus, to the computer system. For compression, the compression device preferably comprises at least one of the following sub-devices:

• • optimal filter,
• • comparators,
• Threshold signal generation devices for generating one or more threshold signals ( SW )
• • differentiator to form derivatives,
• Integrator for forming integrated signals,
• • other filters,
• Envelope generator for generating an envelope signal from the received signal,
• • Correlation filter to compare the received signal or derived signals with reference signals.

In a particularly simple form, the proposed method for transmitting sensor data, in particular an ultrasonic sensor, from a sensor to a computer system, in particular in a vehicle, is carried out as follows:

It starts by sending out an ultrasonic burst. This is followed by the reception of an ultrasound signal, that is to say typically a reflection and the formation of a time-discrete received signal consisting of a temporal sequence of sampled values. Each sample value is assigned a time date (time stamp). This typically reflects the timing of the scan. On the basis of this data stream, the determination of a first parameter signal of a first property takes place with the aid of a first filter from the sequence of sample values of the received signal. In this case, the parameter signal is preferably formed again as a time-discrete sequence of parameter signal values. Each parameter signal value is again assigned exactly one time date (time stamp). Preferably, this datum corresponds to the most recent time datum of a sample used to form that particular parameter signal value. Concurrently with time, the determination of at least one further parameter signal of a property assigned to this further parameter signal preferably takes place with the aid of a further filter assigned to this further parameter signal from the sequence of sampled values of the received signal, wherein the further parameter signals are again formed as time-discrete sequences of further parameter signal values. Here too, each further parameter signal value is assigned the same time date (time stamp) as the corresponding parameter signal value.

The first parameter signal and the further parameter signals are collectively referred to below as a feature vector signal. This feature vector signal (or else parameter vector signal) thus represents a time-discrete sequence of feature vector signal values, which consist of the parameter signal values and further parameter signal values, each with the same time date (time stamp). Thus, each respective time-related date (time stamp) can be assigned to each feature vector signal value (= parameter signal value) thus formed.

The comparison of the feature vector signal values of a temporal datum (time stamp) with a threshold value vector, which is preferably a prototype vector, then takes place quasi-continuously, with the formation of a Boolean result which can have a first and a second value. For example, it is conceivable compare the magnitude of the current feature vector signal value representing, for example, a first component of a feature vector signal value, with a fifteenth threshold representing a first component of the threshold vector and set the boolean result to a first value, if The magnitude of the feature vector signal value is less than this fifteenth threshold, and a second value if it is not. If the Boolean result has a first value, then it is further conceivable to determine the magnitude of the further feature vector signal value, which represents, for example, a further component of this feature vector signal, with a further threshold value, which represents a further component of the threshold vector and to leave the Boolean result at the first value if the magnitude of the further feature vector signal value is less than this further threshold, and set the Boolean result to the second value if not. In this way all other feature vector signal values can be checked. Of course, other classifiers are conceivable. Also, the comparison with several different threshold vectors is possible. These threshold vectors thus represent the prototypes of given signal forms. They originate from the said library. Each threshold vector is again preferably assigned a symbol.

The last step in this case is then to transmit the symbol and possibly also the feature vector signal values and the temporal date (time stamp) associated with this symbol or feature vector signal value from the sensor to the computer system, if the Boolean result has the first value for this time date (time stamp).

Thus, all other data is no longer transmitted. Furthermore, the multi-dimensional evaluation avoids disturbances.

On this basis, a sensor system is thus proposed with at least one computer system which is capable of carrying out one of the methods presented above and with at least two sensors which are likewise capable of carrying out one of the previously presented methods, so that these have at least two sensors With the computer system can communicate by Signalobjekterkennung and are also in a position to transmit third-party echoes compact and make this information additional to the computer system available. Accordingly, the sensor system is typically provided for that the data transmission between the at least two sensors and the computer system can take place or run according to the methods described above. Within the at least two sensors of the sensor system, an ultrasound receiving signal, that is to say at least two ultrasound receiving signals, is typically compressed by means of one of the previously proposed methods and transmitted to the computer system. In this case, the at least two ultrasonic reception signals are reconstructed into reconstructed ultrasonic reception signals within the computer system. The computer system then performs object recognition of objects in the vicinity of the sensors with the aid of reconstructed ultrasound reception signals. The sensors thus do not perform this object recognition, in contrast to the prior art.

The computer system preferably additionally performs, with the aid of the reconstructed ultrasonic received signals and additional signals of further sensors, in particular the signals of radar sensors, an object recognition of objects in the vicinity of the sensors.

As a last step, the computer system based on the detected objects preferably creates an environment map for the sensors or a device whose part is the sensors.

Advantage of the invention

Such a compressed transmission of data via the data bus between the sensor and the computer system reduces the data bus load and thus the criticality with respect to EMC requirements and also provides free data bus capacities during the reception time for the transmission of control commands from the computer system to the sensor and for transmitting status information and other data from the sensor to the computer system. The proposed prioritization ensures that security-relevant data is transmitted first and thus no unnecessary dead times of the sensor arise.

list of figures

• 1 shows the basic procedure of the signal compression and the transmission (description see above);
• 2 shows in more detail the basic procedure of signal compression and transmission (see description above);
• 3 a shows a conventional ultrasonic echo signal ( 1 ) and its conventional evaluation.
• 3 b shows a conventional ultrasonic echo signal ( 1 ) and its evaluation, wherein the amplitude is mitübertrag.
• 3c shows an ultrasonic echo signal containing the chirp direction.
• 3d shows detected signal objects (triangular signals) in the signal of 1c by throwing unrecognized signal components.
• 4e shows the unclaimed conventional transmission
• 4f shows the unstressed transmission of analyzed data after complete reception of the ultrasonic echo
• 4g shows the claimed transmission of compressed data, in which example symbols for signal primitives are largely without compression according to the prior art.
• 5h shows the claimed transmission of compressed data, in which example symbols for signal primitives are compressed into symbols for signal objects.
• 6 shows the claimed transmission of compressed data, in which example symbols for signal primitives are compressed into symbols for signal objects. Not only the envelope signal but also the confidence signal is evaluated.

Description of the other figures

The 1 and 2 have already been described above.

3 a 3a shows the unclaimed time course of a conventional ultrasonic echo signal ( 1 ) and its unclaimed conventional evaluation in freely chosen units. Starting with the transmission of the transmission burst ( SB ), a threshold signal ( SW ). Whenever the envelope signal of the ultrasonic echo signal ( 1 ) the threshold signal ( SW ), the output ( 2 ) is set to logical 1. It is a temporally analogous Interface with a digital output level. The further evaluation is then taken over in the control unit of the sensor. A signaling of errors or control of the sensor is not possible over this analog prior art interface.

3 b 3b shows the unclaimed time course of a conventional ultrasonic echo signal ( 1 ) and its unclaimed conventional evaluation in freely chosen units. Starting with the transmission of the transmission burst ( SB ), a threshold signal ( SW ). Whenever the envelope signal of the ultrasonic echo signal ( 1 ) the threshold signal ( SW ), the output ( 2 ) but now set to a level corresponding to the amplitude of the detected reflection. It is a temporally analog interface with an analog output level. The further evaluation is then taken over in the control unit of the sensor. A signaling of errors or control of the sensor is not possible over this analog prior art interface.

3c shows for explanation the ultrasonic echo signal, wherein the chirp direction (eg A = chirp-up, B = chirp down) is marked.

3d In 3d the principle of symbolic signal transmission is explained. Instead of the signal 3c For example, only two types of triangular objects are transmitted here. Specifically, these are a first triangle object ( A ) for the chirp-up case and a second triangle object ( B ) for the chirp-down case. At the same time, the timing and amplitude of the triangle object are transmitted. If a reconstruction of the signal takes place on the basis of this data, a signal is obtained correspondingly 3d , From this signal, the signal components were removed that did not correspond to the triangular signals. There is thus a throw of unrecognized signal components and massive data compression.

4e shows the unclaimed conventional analog transmission of the intersections of the envelope signal ( 1 ) of the ultrasonic echo signal with the threshold signal ( SW ).

4f shows the unstressed transmission of analyzed data after complete reception of the ultrasonic echo.

4g shows the claimed transmission of compressed data, in which example symbols for signal primitives are transmitted largely without compression.

5h shows the claimed transmission of compressed data, in which example symbols for signal primitives are compressed into symbols for signal objects. First, a first triangle object ( 59 ) characterized by the characteristic temporal sequence of a threshold exceeded followed by a maximum and a threshold undershoot detected and transmitted. Then a double point with saddle point ( 60 ) above the threshold signal. Characteristic here is the sequence of exceeding the threshold signal ( SW ) by the envelope signal ( 1 ) followed by a maximum of the envelope signal ( 1 ) followed by a minimum above the threshold signal ( SW ) followed by a maximum above the threshold signal ( SW ) followed by an undershoot of the threshold signal ( SW ). After recognition, the symbol for this twin point with saddle point is transmitted. A timestamp is also transferred. Preferably, other parameters of the double peak with saddle point are also transmitted, such as the positions of the maxima and of the minimum, or a scaling factor. It then follows again the detection of a triangular signal as a basic signal object as exceeding the threshold signal ( SW ) by the envelope signal followed by a maximum of the envelope signal followed by a falling below the threshold signal ( SW ) through the envelope signal. It then follows again the detection of a double peak but now the minimum of the envelope signal below the threshold signal ( SW ) lies. This dual tip can thus be treated, for example, as a separate signal object, if necessary. As can easily be seen, this treatment of the signal leads to a massive data reduction.

6 shows the claimed transmission of compressed data accordingly 3 In this example, not only the envelope signal but also the confidence signal is evaluated.

LIST OF REFERENCE NUMBERS

α

Emitting the ultrasonic burst;

β

Receiving the ultrasonic burst reflected on an object and converting it into an electrical received signal;

γ

Compression of the received electrical signal;

γa

Sampling the electrical input signal and forming a sampled electrical input signal, wherein preferably a time stamp can be assigned to each sample of the electrical input signal.

γb

Determination of several spectral values, eg by matched filter for prototypical signal object classes. These several Spectral values together form a feature vector. This formation preferably takes place continuously, resulting in a stream of feature vector values. Each feature vector value may preferably be assigned a time stamp value again;

y c

optional, but preferably performed normalization of the feature vector spectral coefficients of the respective feature vector of a time stamp value before the correlation with the prototypical signal object classes in the form of predefined prototype feature vector values of a prototype library;

γd

Distance determination between the current feature vector value and the values of the prototypical signal object classes in the form of predefined prototype feature vector values of a prototype library;

γe

Selection of the most similar prototypical signal object class in the form of a predetermined prototype feature vector value of a prototype library with preferably minimal distance from the current feature vector and adoption of the symbol of this signal object class as recognized signal object together with the timestamp value as compressed data. Possibly. Further data, in particular signal object parameters, such as e.g. whose amplitude is taken over as compressed data. This compressed data then forms the compressed received signal;

δ

Transmission of the compressed electrical received signal to the computer system:

1

Envelope of the received ultrasonic signal;

2

Output signal (transmitted information) of an IO interface according to the prior art;

3

transmitted information of a LIN interface according to the prior art;

4

exemplary, first intersection of the envelope ( 1 ) of the received signal with the threshold signal ( SW ) in the downward direction .;

5

exemplary, first intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction;

6

exemplary first maximum of the envelope ( 1 ) above the threshold signal ( SW );

7

exemplary, second intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction;

8th

exemplary, second intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction;

9

exemplary second maximum of the envelope ( 1 ) above the threshold signal ( SW );

10

exemplary first minimum of the envelope ( 1 ) above the threshold signal ( SW );

11

exemplary third maximum of the envelope ( 1 ) above the threshold signal ( SW );

12

exemplary, third intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction;

13

exemplary, third intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction;

14

exemplary fourth maximum of the envelope ( 1 ) above the threshold signal ( SW );

15

exemplary, fourth point of intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction;

16

exemplary, fourth point of intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction;

17

exemplary fifth maximum of the envelope ( 1 ) above the threshold signal ( SW );

18

exemplary, fifth point of intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction;

19

exemplary, fifth point of intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction;

20

exemplary sixth maximum of the envelope ( 1 ) above the threshold signal ( SW );

21

exemplary, sixth intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction;

22

exemplary, sixth intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction;

23

exemplary seventh maximum of the envelope ( 1 ) above the threshold signal ( SW );

24

exemplary seventh intersection of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction;

25

Envelope during the ultrasonic burst

26

Transmission of the data of the exemplary first intersection ( 4 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction over the preferably bidirectional data bus;

27

Transmission of the data of the exemplary first intersection ( 5 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction over the preferably bidirectional data bus;

28

Transmission of the data of the exemplary first maximum ( 6 ) of the envelope ( 1 ) above the threshold signal ( SW ) via the preferably bidirectional data bus;

29

Transmission of the data of the exemplary second intersection ( 7 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction over the preferably bidirectional data bus;

30

Transmission of the data of the exemplary second intersection ( 8th ) of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction over the preferably bidirectional data bus;

31

Transmission of the data of the exemplary second maximum ( 9 ) of the envelope ( 1 ) above the threshold signal ( SW ) and the data of the exemplary first minimum ( 10 ) of the envelope ( 1 ) above the threshold signal ( SW ) via the preferably bidirectional data bus;

32

Transmission of the data of the exemplary third maximum ( 11 ) of the envelope ( 1 ) above the threshold signal ( SW ) via the preferably bidirectional data bus;

34

Transmission of the data of the exemplary third point of intersection ( 12 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction over the preferably bidirectional data bus;

35

Transmission of the data of the exemplary third point of intersection ( 13 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction over the preferably bidirectional data bus;

36

Transmission of the data of the exemplary fourth maximum ( 14 ) of the envelope ( 1 ) above the threshold signal ( SW ) via the preferably bidirectional data bus;

37

Transmission of the data of the exemplary, fourth intersection point ( 15 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction over the preferably bidirectional data bus;

38

Transmission of the data of the exemplary, fourth intersection point ( 16 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction over the preferably bidirectional data bus;

39

Transmission of the data of the exemplary fifth maximum ( 17 ) of the envelope ( 1 ) above the threshold signal ( SW ) via the preferably bidirectional data bus;

40

Transmission of the data of the exemplary fifth intersection ( 18 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction over the preferably bidirectional data bus;

41

Transmission of the data of the exemplary, fifth point of intersection ( 19 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the upward direction over the preferably bidirectional data bus;

42

Transmission of the data of the exemplary sixth point of intersection ( 21 ) of the envelope ( 1 ) with the threshold signal ( SW ) in the downward direction over the preferably bidirectional data bus;

43

Transmitting the data of the received echoes on the LIN bus in the prior art after the end of the reception;

44

Transmission of data on the prior art LIN bus prior to transmission of the ultrasonic burst;

45

Transmission of data via the prior art IO interface prior to transmission of the ultrasonic burst;

46

Effect of the ultrasound transmit burst on the output signal of the IO interface according to the prior art;

47

Signal of the first echo ( 5 . 6 . 7 ) on the IO interface acc. the prior art;

48

Signal of the second echo ( 8th . 9 . 10 . 11 . 12 ) on the IO interface acc. the prior art;

49

Signal of the third and fourth echo ( 13 . 14 . 15 ) on the IO interface acc. the prior art;

50

Signal of the fifth echo ( 16 . 17 . 18 ) on the IO interface acc. the prior art;

51

Signal of the sixth echo ( 19 . 20 . 21 ) on the IO interface acc. the prior art;

52

Signal of the seventh echo ( 22 . 23 . 24 ) on the IO interface acc. the prior art;

53

Start command from the computer system to the sensor via the data bus;

54

periodic automatic data transmission between sensor and computer system preferably according to DSI3 standard;

55

Diagnostic bits after the measurement cycle;

56

End of emission of ultrasonic burst (end of transmit burst). Preferably, the end of the ultrasonic burst coincides with the point 4 together.

57

Start of emission of the ultrasonic burst (beginning of the transmission burst).

58

End of data transfer

a

Transmitted information for the transmission of the received ultrasonic echoes by means of a prior art I / O interface;

A

Exemplary recognized object with chirp-down;

a.u.

"Arbritrary units" = freely chosen units

B

Exemplary recognized object with chip-up;

b

Transmitted information for the transmission of the received ultrasonic echoes by means of a LIN interface from the prior art;

c

Transmitted information for the transmission of the received ultrasonic echoes by means of the proposed method and the proposed device with envelope for comparison;

d

Transmitted information for the transmission of the received ultrasonic echoes by means of the proposed method and the proposed device without an envelope;

e

schematic waveforms in the transmission of the received echo information by means of an IO interface from the prior art;

s

Amplitude of the envelope of the received ultrasonic signal;

f

schematic waveforms in the transmission of the received echo information by means of a LIN interface from the prior art;

G

schematic waveforms in the transmission of the received echo information by means of a bidirectional data interface;

SB

Transmission burst

SW

threshold

t

Time;

T _E

Reception time. The reception time typically begins with the end ( 56 ) emitting the ultrasonic burst. It is possible to start reception before. However, this can lead to problems that may require additional measures.

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• WO 2012/016834 A1 [0004]
• DE 4433957 A1 [0005]
• DE 102012015967 A1 [0006]
• DE 102011085286 A1 [0007]
• WO 2014108300 A1 [0008]
• DE 102015104934 A1 [0009]
• DE 102015104934 A [0009]
• DE 102010041424 A1 [0011]
• DE 102013226373 A1 [0012]
• US 2006/0250297 A1 [0013]
• DE 102017100837 [0043]
• DE 102017100835 [0043]

Claims (26)

Method for transmitting sensor data, in particular an ultrasonic sensor, from a sensor to a computer system, in particular in a vehicle, comprising or comprising the steps - emitting an ultrasonic burst; Receiving an ultrasonic signal and forming an ultrasonic received signal; Forming a feature vector signal from the ultrasonic received signal; Detecting signal objects and classifying these signal objects into acknowledged signal object classes within the ultrasonic received signal, a signal object comprising the combination of two or three or four or more signal basic objects, and Whereby at least one assigned signal object parameter and one symbol corresponding to the signal object class assigned to this signal object are assigned to each signal object thus recognized and classified Wherein each signal object thus recognized and classified is determined at least one associated signal object parameter and a symbol for that signal object; Transmitting at least the symbol of a recognized signal object class and at least of the one associated signal object parameter of this detected signal object class. Method according to Claim 1 comprising the additional step - determining a chirp value as the associated signal object parameter, which indicates whether the detected signal object is an echo of an ultrasound transmit burst with chirp-up or a chirp-down or a no-chirp properties , Method according to one or more of Claims 1 to 2 comprising the additional step - generating a confidence signal by forming a correlation between the received signal or a signal derived therefrom on the one hand and a reference signal on the other hand. Method according to one or more of Claims 1 to 3 comprising the additional step - generating a phase signal. Method according to Claim 4 comprising the additional step of - generating a phase confidence signal by forming the correlation between the phase signal or a signal derived therefrom on the one hand and a reference signal. Method according to Claim 5 comprising the additional step of comparing the phase confidence signal with one or more thresholds to produce a discretized phase confidence signal. Method according to one or more of Claims 1 to 6 - where at least one signal object class is a wavelet. Method according to Claim 7 - wherein the at least one wavelet is a triangle wavelet. Method according to one or more of Claims 7 to 8th - Wherein the at least one wavelet is a rectangular wavelet. Method according to one or more of Claims 7 to 9 - wherein the at least one wavelet is a sine half-wave wavelet. Method according to one or more of Claims 7 to 10 wherein one of the signal object parameters is a time shift of the wavelet of the detected signal object or is a temporal compression or stretching of the wavelet of the detected signal object or an amplitude of the wavelet of the detected signal object. Method according to one or more of Claims 1 to 11 - Wherein the transmission of error states of the sensor • against the transmission of the at least one detected signal object class and / or • takes place prior to the transmission of the one associated signal object parameter higher priority. Method according to Claim 12 - wherein a basic signal object is the crossing of the magnitude of the amplitude of the envelope signal (1) with the amount of a threshold signal (SW) at a crossing time. Method according to one or more of Claims 1 to 13 - Wherein a basic signal object crossing the amount of the amplitude of the envelope signal (1) with the amount of a threshold signal (SW) at a crossing time in the ascending direction. Method according to one or more of Claims 1 to 14 - wherein a basic signal object is the crossing of the magnitude of the amplitude of the envelope signal (1) with the amount of a threshold signal (SW) at a crossing time in the descending direction. Method according to one or more of Claims 1 to 15 - wherein a basic signal object is a maximum of the magnitude of the amplitude of the envelope signal (1) above the magnitude of a threshold signal (SW) at a maximum time. Method according to one or more of Claims 1 to 16 - wherein a basic signal object is a minimum of the magnitude of the amplitude of the envelope signal (1) above the magnitude of a threshold signal (SW) at a minimum time. Method according to one or more of Claims 1 to 17 wherein a basic signal object is a predefined chronological sequence and / or temporal grouping of other basic signal objects. Method according to one or more of Claims 1 to 18 - wherein transmitting at least the symbol of a detected signal object class and at least one associated signal object parameter of this detected signal object class is the transmission of the signal object class of a signal object, which is a predefined temporal sequence of other signal objects, and wherein at least one signal object class of at least one of these other signal objects is not transmitted , Sensor, in particular ultrasonic sensor, for carrying out a method according to one or more of Claims 1 to 19 suitable or intended. Computer system for carrying out a method according to one or more of Claims 1 to 19 suitable or intended. Sensor system - with at least one computer system after Claim 21 and - with at least two sensors after Claim 20 wherein the sensor system is provided so that the data transmission between the sensors and the computer system according to a method according to one or more of Claims 1 to 19 expires or expires. Sensor system after Claim 22 - Wherein within the sensors in each case an ultrasonic signal received, that is, at least two ultrasonic received signals, by means of a method according to a method according to one or more of Claims 1 to 19 is compressed and transmitted to the computer system and - wherein the at least two ultrasonic reception signals are reconstructed to reconstructed ultrasonic reception signals within the computer system. Sensor system after Claim 23 - Wherein the computer system by means of reconstructed ultrasonic received signals performs an object detection of objects in the environment of the sensors. Sensor system after Claim 24 - Wherein the computer system by means of reconstructed ultrasonic received signals and additional signals of other sensors, in particular signals from radar sensors, performs an object detection of objects in the environment of the sensors. Sensor system according to one or more of Claims 24 or 25 - Wherein the computer system based on the detected objects creates an environment map for the sensors or a device of which the sensors are part.

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