Apparatus and method for adaptive analog-to-digital conversion of sensor signals

Abstract

The invention relates to an apparatus and a method for adaptive analog-to-digital conversion of sensor signals. The present disclosure proposes an analog-to-digital conversion (ADC) circuit (30) for a sensor signal, comprising: an input interface (31) configured to receive an analog sensor signal; an analog-to-digital converter (32) configured to digitize the analog sensor signal to obtain samples of the digital sensor signal; a digital filter (34) configured to average a number of samples of the digital sensor signal to obtain an averaged sensor signal; a processor (36) configured to adjust the averaged number of samples based on one or more characteristics of the analog sensor signal or the digital sensor signal to obtain an averaged sensor signal; and an output interface (38) for averaging the sensor signals.

Description

Technical Field

[0001] The present disclosure relates generally to analog-to-digital conversion (ADC) circuits, and more particularly to adapted ADC circuits for improved power consumption and noise. Background Art

[0002] 3D Hall sensor is a type of sensor technology that can be used in joysticks, gear shifters and other input or control devices to detect the position of the device in three-dimensional (3D) space. It relies on the Hall effect, which is a physical phenomenon that occurs when a magnetic field interacts with a conductive material, producing a voltage that can be measured and used to determine the position of the magnet.

[0003] Inside the joystick or gear lever, a small magnet can be attached to the moving part of the lever, and the sensor is placed in a nearby fixed position. The sensor can be a 3D Hall effect sensor. As the lever moves, the position of the magnet changes relative to the sensor. The Hall sensor detects the change in magnetic field strength caused by the movement of the magnet. When the magnet moves, the Hall sensor generates a voltage output proportional to the strength and direction of the magnetic field. The voltage output can then be processed by an electronic device that may include one or more analog-to-digital converters (ADCs). The electronic device of the lever uses the voltage output from the Hall sensor to calculate the position of the lever in three dimensions (usually the X-axis, Y-axis, and Z-axis). In particular, an application (such as a gear lever controller) can receive a digital value proportional to the voltage sensed at the output of the Hall element. The Hall sensor may include one or more Hall elements and a signal path for adjusting the voltage output. The signal path may include an analog-to-digital converter (ADC) (plus an optional digital filter) so that the final output of the Hall sensor is a digital interface.

[0004] This information can then be used, for example, to control on-screen movement or interact with software and games.

[0005] Similar to other electronic sensors, Hall sensors may be susceptible to noise. Noise refers to any undesired electrical disturbance or fluctuation in the sensor output signal in this article, which may distort the measurement or add uncertainty to the measurement. Several factors may cause noise in the Hall sensor reading. For example, the Hall sensor may be affected by an external magnetic field, which may introduce noise into the measurement of the Hall sensor. Strong magnets nearby or electromagnetic interference (EMI) from other devices may disrupt the reading of the sensor. Further, due to factors such as power supply fluctuations, grounding problems, and electromagnetic interference from nearby electronic components, electronic circuits may introduce electrical noise. The quality of the Hall sensor itself may also affect its noise sensitivity. Compared with higher quality sensors with better shielding and noise resistance characteristics, low-quality sensors may be more prone to noise.

[0006] To mitigate noise in Hall sensor measurements, shielding the sensor and its wiring can help protect the sensor from external magnetic fields and reduce electromagnetic interference. Implementing filtering techniques such as low-pass filters can also help remove high-frequency noise from the sensor output. However, such filtering techniques may come with increased measurement time and, therefore, higher current consumption for measurement. For another example, due to its low average current consumption requirements, the sensor may not perform continuous measurements (it only performs measurements when triggered on the digital interface or when configured to periodically self-trigger).

[0007] Users also often demand less energy consumption. For example, in automotive applications, for example, for the driving range of electric vehicles, the total current consumption should be reduced. For battery-driven devices, the current consumption should be reduced to extend the usable time.

[0008] Thus, for example for Hall sensors and other sensors, there may be a need to optimize energy consumption and noise. Summary of the invention

[0009] This need is solved by an apparatus and a method according to the appended claims.

[0010] According to a first aspect, the present disclosure provides an ADC circuit for a sensor signal. The ADC circuit includes an input interface, which is configured to receive an analog sensor signal. The ADC circuit includes an ADC, which is configured to digitize the analog sensor signal to obtain a digital sensor signal sample. The ADC circuit includes a digital filter, which is configured to average several samples of the digital sensor signal to obtain an average sensor signal. The ADC circuit further includes a processor (e.g., a control module), which is configured to adjust (adapt) the number of averaged samples based on one or more characteristics of the analog sensor signal or the digital sensor signal to obtain the average sensor signal. The ADC circuit further includes an output interface for the average sensor signal.

[0011] Embodiments of the present disclosure may allow for adjustment of the number of samples averaged and therefore filtered based on one or more characteristics of the sensor signal.

[0012] In some embodiments, the characteristics of the digital sensor signal include the signal strength and / or signal dynamics of the analog sensor signal or the digital sensor signal. The signal strength indicates the strength and amplitude of the sensor signal. "Signal dynamics" may refer to the dynamic range of the sensor signal. The dynamic range is the difference between the minimum and maximum values ​​that the sensor signal can represent. In digital signal processing, it may refer to the range of values ​​that can be accurately represented by the number of bits used to encode the signal. A wider dynamic range allows a wider range of signal amplitudes to be represented. "Signal dynamics" may also refer to the changing or time-varying characteristics of the sensor signal. Signals are typically not static, but rather vary over time. These changes may include changes in amplitude, frequency, phase, or other properties. A higher signal strength may require fewer average samples than a lower signal strength. Similarly, a higher or greater signal dynamic may require fewer average samples than a lower signal dynamic.

[0013] In some embodiments, the processor is configured to determine a signal strength of the digital sensor signal and adjust the number of samples averaged based on the signal strength.For example, the signal strength may be determined based on the amplitude or power of the digital sensor signal.

[0014] In some embodiments, the processor is configured to decrease the number of averaged samples if the signal strength increases and to increase the number of averaged samples if the signal strength decreases.

[0015] In some embodiments, the processor is configured to compare the determined signal strength to one or more predefined thresholds and select the number of samples to be averaged based on the comparison.

[0016] In some embodiments, the processor is configured to determine signal dynamics of the digital sensor signal and adjust the number of averaged samples used to obtain the average sensor signal based on the signal dynamics.For example, the signal dynamics may be determined based on a rate of change (deviation) of the digital sensor signal.

[0017] In some embodiments, the processor is configured to decrease the number of averaged samples if the signal dynamically increases, and to increase the number of averaged samples if the signal dynamically decreases.

[0018] In some embodiments, the processor is configured to compare the determined signal dynamics to one or more predefined thresholds and select the number of samples to be averaged based on the comparison.

[0019] In some embodiments, the ADC circuit further includes a selector configured to select one or more characteristics of the analog sensor signal or the digital sensor signal based on which the number of samples to be averaged is adjusted. For example, the selector can be configured to select signal strength, signal dynamics, or both as signal characteristics.

[0020] In some embodiments, the ADC comprises a sigma-delta ADC (ΣΔ-ADC). ΣΔ-ADC is a type of analog-to-digital converter that can be used for high resolution, high precision, and low frequency applications.

[0021] In some embodiments, the ADC circuit further comprises a magnetic field sensor coupled to the input interface to provide an analog magnetic field sensor signal. For example, the magnetic field sensor may comprise a 3D Hall sensor.

[0022] According to another aspect, the present disclosure provides a method for analog-to-digital conversion of a sensor signal. The method includes receiving an analog sensor signal; digitizing the analog sensor signal to obtain samples of a digital sensor signal; averaging several samples of the digital sensor signal to obtain an average sensor signal, adjusting (adapting) the number of averaged samples based on one or more characteristics of the analog sensor signal or the digital sensor signal to obtain the average sensor signal; and outputting the average sensor signal.

[0023] According to another aspect, the present disclosure provides an ADC circuit for a sensor signal. The ADC circuit includes an input interface configured to receive an analog sensor signal, an ADC configured to digitize the analog sensor signal to obtain samples of a digital sensor signal, a digital filter configured to filter several samples of the digital sensor signal to obtain a filtered digital sensor signal, a processor configured to adjust a bandwidth of the digital filter based on one or more characteristics of the digital sensor signal, and an output for filtering the digital sensor signal.

[0024] In some embodiments, the processor is configured to determine a signal strength of the digital sensor signal and adjust a bandwidth of the digital filter based on the signal strength.

[0025] In some embodiments, the processor is configured to increase the bandwidth of the digital filter if the signal strength increases and to decrease the bandwidth of the digital filter if the signal strength decreases.

[0026] In some embodiments, the processor is configured to compare the signal strength to one or more predefined thresholds and select a bandwidth of the digital filter based on the comparison.

[0027] In some embodiments, the processor is configured to determine signal dynamics of the digital sensor signal and adjust a bandwidth of the digital filter based on the signal dynamics.

[0028] In some embodiments, the processor is configured to increase the bandwidth of the digital filter if the signal dynamics increase, and to decrease the bandwidth of the digital filter if the signal dynamics decrease. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Some examples of apparatus and / or methods will be described below, by way of example only, with reference to the accompanying drawings, in which:

[0030] Figure 1 shows different components of the magnetic field at the location of the magnetic sensor depending on the inclination of the moving part;

[0031] Figure 2 The dependence of noise and measurement timing is illustrated;

[0032] Figure 3 A block diagram showing an ADC circuit for a sensor signal according to an embodiment; and

[0033] Figure 4 The effect of the proposed adaptive analog-to-digital conversion is illustrated.

[0034] Specific implementation method

[0035] Some examples are now described in more detail with reference to the accompanying drawings. However, other possible examples are not limited to the features of these embodiments described in detail. Other examples may include modifications of features and equivalents or substitutes of features. In addition, the terms used to describe some examples herein should not limit other possible examples.

[0036] Throughout the description of the drawings, the same or similar reference numerals refer to the same or similar elements and / or features, which may be equivalent or implemented in a modified form while providing the same or similar functions. For clarity, the thickness of the lines, layers and / or regions in the drawings may also be exaggerated.

[0037] When two elements A and B are combined using "or", this should be understood to disclose all possible combinations, i.e. only A, only B, and A and B, unless otherwise clearly defined in individual cases. "At least one of A and B" or "A and / or B" can be used as alternative terms for the same combination. It is equally applicable to combinations of more than two elements.

[0038] If a singular form, such as "a", "an", "the", is used, and the use of only a single element is not explicitly or implicitly defined as mandatory, other examples may also use several elements to implement the same functionality. If a functionality is described below as being implemented using multiple elements, other examples may use a single element or a single processing entity to implement the same functionality. It should also be understood that when the terms "include", "including", and / or "comprise", "comprising", are used, the presence of specified features, integers, steps, operations, processes, elements, components, and / or groups thereof is described, but the presence or addition of one or more other features, integers, steps, operations, processes, elements, components, and / or groups thereof is not excluded.

[0039] Figure 1 A 3D magnetic position sensor 10 (e.g., a 3D Hall Effect sensor) on a substrate 12 is schematically illustrated. For example, the substrate 12 may be a printed circuit board (PCB). The 3D magnetic position sensor 10 may be a device that detects magnetic field strength in the x-axis, y-axis, and z-axis. It may measure three-dimensional, linear, angular, and rotational movement, and transmit data via an output interface.

[0040] The permanent magnet 14 is attached to the moving part 16 of the joystick or gear lever. Those skilled in the art who benefit from the present disclosure will understand that other applications (such as multi-function steering wheels, multi-function knobs or pedal / valve position sensing) are also feasible. In the illustrated example, the 3D magnetic sensor 10 is located in a fixed position below the magnet 14. The Hall effect, a long-standing method of measuring magnetic fields, achieves a measurable voltage by placing the magnet 14 perpendicular to a flat conductor. The charge carriers carrying the current throughout the conductor are disturbed by the magnetic field of the magnet, and its protons and electrons jump to opposite sides. With the positive and negative charges separated, the meter can quantitatively measure the voltage of the conductor. When the power of the magnetic field changes, the 3D Hall effect position sensor 10 linked to the magnet 14 can relay the signal.

[0041] Figure 1 It is further shown that the dependence of the inclination angle θ of the mobile part 16 in the x direction x Different components of the magnetic field at the magnetic sensor location. Figure 1 It can be seen that the z component of the magnetic field at the magnetic sensor position (B z ) can be at an inclination angle Θ x =0° has its peak value (75 mT). Therefore, for B in the center position of the moving part 16 Z Noise may not be important because B z ≈75mT. The y component of the magnetic field at the location of the magnetic field sensor (By ) can be 0 and is independent of the inclination angle θ x The x-component of the magnetic field at the location of the magnetic field sensor (B x ) at an inclination angle Θ x =0° can be 0, Θ x <0°B x < 0, and Θ x >0°B x >0. Therefore, the noise is B in the center position of the moving part 16 x and B y is more important because B x ≈B y ≈0mT. In general, it can be found that noise is less important at high magnetic field strengths, while it is more important at low magnetic field strengths.

[0042] Figure 2 The figure shows how the noise depends on the measurement timing.

[0043] With B x , B y , B z The corresponding analog sensor signal (e.g., Hall voltage) can be fed to an internal ADC or an external ADC to obtain samples of the digital sensor signal. The internal digital filter of the 3D Hall effect position sensor 10 can be configured to average several samples of the digital sensor signal to obtain an average sensor signal. The measurement timing corresponds to the number of samples used for averaging. Figure 2 It can be seen that for B x , B y , B z The measurement noise of decreases as the number of samples used for averaging increases. The longer the measurement (the higher the number of samples), the lower the noise. However, the longer the measurement (the higher the number of samples), the higher the energy consumption of the 3D Hall effect position sensor 10.

[0044] For example, embodiments of the present disclosure provide for adapting measurement / conversion time and / or filter bandwidth according to one or more sensor signal characteristics, such as signal-to-noise ratio (SNR).

[0045] Figure 3 An example of an ADC circuit 30 for sensor signals according to an embodiment of the present disclosure is shown. For example, the ADC circuit 30 can be used as part of an integrated sensor circuit (sensor IC). In particular, the ADC circuit 30 can be used as part of an integrated 3D Hall effect position sensor circuit.

[0046] The ADC circuit 30 includes an input interface 31 configured to receive an analog sensor signal from a sensor 40. For example, the sensor 40 may be implemented as a separate IC or may be implemented together with the ADC circuit 30 in a common semiconductor package. For example, in the case of a Hall sensor, the analog sensor signal may be an analog Hall voltage. For example, the analog sensor signal may be connected to a B x , B y , B z Other magnetic sensors (such as magnetoresistive sensors) may also be used as signal sources.

[0047] The ADC circuit 30 further comprises an ADC 32 configured to digitize the analog sensor signal from the input interface 31 to obtain samples of the digital sensor signal at the output of the ADC 32. The ADC 32 is configured to digitize the analog sensor signal from the input interface 31 to obtain samples of the digital sensor signal at the output of the ADC 32. s The analog sensor signal is obtained at discrete snapshots or samples. The rate at which samples are obtained is 1 / T. s is called the sampling rate or sampling frequency of the ADC. Figure 3 ADC 32 is depicted as a ΣΔ-ADC, but skilled artisans having the benefit of this disclosure will appreciate that other ADC implementations are possible, such as a successive approximation ADC (SAR ADC), a flash ADC, or a pipeline ADC.

[0048] Downstream of the ADC 32, the ADC circuit 30 further comprises a digital filter 34 which is configured to average several samples of the digital sensor signal to obtain an average sensor signal at the output of the digital filter 34. In the case of n averaged samples, the conversion time of the ADC circuit 30 is substantially the same as n. . T s Correspondingly, T s The sampling time interval of the ADC 32 is marked. For example, the digital filter 34 can be implemented as a finite impulse response (FIR) filter or an infinite impulse response (IIR) filter. For example, the digital filter 34 can be a low-pass, band-pass, high-pass or notch filter. According to the present disclosure, it can be an adaptive filter because the number of averaged samples used to average the sensor signal and / or its filter bandwidth can be adjusted.

[0049] For this adjustment, the ADC circuit 30 further includes a processor 36 configured to adjust the number of averaged samples in the digital filter 34 to obtain the average sensor signal. The number of averaged samples can be adjusted based on one or more characteristics of the analog sensor signal or the digital sensor signal. The signal characteristics can be obtained by analyzing the analog signal at the input of the ADC 32, the samples of the digital sensor signal at the output of the ADC 32, the averaged sensor signal at the output of the digital filter 34, or a combination thereof.

[0050] The signal characteristics of the sensor signal may include the signal strength and / or signal dynamics of the analog sensor signal or the digital sensor signal. For example, the processor (e.g., the control module or the adaptation configuration module) 36 may be configured to measure the amplitude of the (non-averaged) sample of the digital sensor signal and / or the amplitude of the average sensor signal. The processor 36 may be configured to determine the signal strength of the digital non-averaged or averaged sensor signal, and adjust the number of averaged samples based on the determined signal strength. The processor 36 may be configured to reduce the number of averaged samples (and thus reduce the conversion time) when the signal strength (e.g., amplitude) increases relative to the aforementioned determined signal strength. For example, the processor 36 may be configured to reduce the number of averaged samples (and thus reduce the conversion time) when the signal strength (e.g., amplitude) of the current output of the digital filter 34 increases relative to one or more of the aforementioned outputs of the digital filter 34. Similarly, the processor 36 may be configured to increase the number of averaged samples (and thus increase the conversion time) when the signal strength (e.g., amplitude) decreases relative to the aforementioned determined signal strength. For example, the processor 36 may be configured to increase the number of averaged samples when the signal strength (e.g., amplitude) of the current output of the digital filter 34 decreases relative to one or more of the aforementioned outputs of the digital filter 34.

[0051] The processor 36 may be configured to compare the determined signal strength to one or more predefined (signal strength) thresholds and select the number of samples to be averaged based on the comparison. That is, the measured signal strength (e.g., amplitude) may be mapped to a predefined number of samples to be averaged. For example, if the measured signal strength falls below a threshold, the number of samples to be averaged may be set to n1. If the measured signal strength exceeds the threshold, the number of samples to be averaged may be set to n2. <n1。

[0052] Additionally or alternatively, the processor 36 can be configured to determine a signal dynamics of the analog sensor signal or the digital sensor signal and adjust the number of samples averaged for obtaining the average sensor signal based on the signal dynamics. For example, the signal dynamics of the sensor signal can include a variance or standard deviation of the analog sensor signal or the digital sensor signal. For example, the processor 36 can be configured to average the number of samples averaged for obtaining the average sensor signal at a conversion time interval n. . Ts The processor 36 may be configured to reduce the number of samples averaged (and thus reduce the conversion time interval) if the signal strength increases relative to the previously determined signal strength. For example, the processor 36 may be configured to reduce the number of samples averaged if the signal dynamics (e.g., variance or standard deviation) increases relative to one or more previously determined values. Similarly, the processor 36 may be configured to increase the number of samples averaged (and thus increase the conversion time) if the signal dynamics (e.g., variance or standard deviation) decrease relative to the previously determined signal dynamics values. For example, the processor 36 may be configured to increase the number of samples averaged if the signal dynamics of the current output of the ADC 32 decrease relative to one or more previously determined outputs of the ADC 32.

[0053] The processor 36 may be configured to compare the determined signal dynamics (e.g., variance or standard deviation) to one or more predefined thresholds and select the number of samples to be averaged based on the comparison. That is, the measured signal dynamics (e.g., variance or standard deviation) may be mapped to a predefined number of samples to be averaged. For example, if the measured signal dynamics (e.g., variance or standard deviation) falls below a threshold, the number of samples to be averaged may be set to n1, and if the measured signal dynamics (e.g., variance or standard deviation) exceeds the threshold, the number of samples to be averaged may be set to n2. <n1。

[0054] The ADC circuit 30 may further include a selector configured to select one or more characteristics of the analog sensor signal or the digital sensor signal (eg, signal strength, signal dynamics) based on which to adjust the number of samples to be averaged.

[0055] For example, as a first option, the selector may select a switching time that depends on the signal strength (eg magnetic field strength)

[0056] Low magnetic field strength → long switching time

[0057] High magnetic field strength → short switching time

[0058] As a second option, the selector can select a switching time that depends on the signal dynamics (e.g. magnetic dynamics) - measurement "n" compared to measurement "n-1"

[0059] High dynamics → noise is less important and switching times can be shorter

[0060] Low dynamic → noise is important for long transition times

[0061] Or several short switching times can be averaged, as long as they are at the same magnetic field level. As a third option, the selector can choose that the two aforementioned concepts can be combined:

[0062] 00 B :

[0063] Default measurement with long conversion time

[0064] 01 B :

[0065] 1. Conversion time depends on magnetic field strength

[0066] 10 B :

[0067] 2. Switching time depends on magnetic dynamics

[0068] 11B:

[0069] 1.+2. Depends on the switching time of magnetic field strength and magnetic dynamics.

[0070] like Figure 3 As can be seen, the ADC circuit 30 further comprises an output interface 38 for outputting the (adapted) average sensor signal. Once the average sensor signal is output, the output interface 38 may trigger a new analog-to-digital conversion including an adaptive averaging process.

[0071] The processor 36 can be configured not only to adjust the number of samples to be averaged. Alternatively or additionally, for example, the processor 36 can be configured to adjust other filter parameters of the digital filter 34 (such as the filter bandwidth of the filter 34) based on one or more characteristics of the digital sensor signal. For example, the processor 36 can be configured to increase the filter bandwidth when the signal dynamics (e.g., variance or standard deviation) increases relative to one or more of the aforementioned determined values. Therefore, the processor 36 can be configured to reduce the filter bandwidth when the signal dynamics (e.g., variance or standard deviation) decreases relative to one or more of the aforementioned determined values. Alternatively or additionally, the processor 36 can be configured to adjust the sampling rate of the ADC 32. For example, the processor 36 can be configured to increase the sampling rate when the signal dynamics (e.g., variance or standard deviation) increases relative to one or more of the aforementioned determined values. Therefore, the processor 36 can be configured to reduce the sampling rate when the signal dynamics (e.g., variance or standard deviation) decreases relative to one or more of the aforementioned determined values.

[0072] Figure 4 The effect of the proposed adaptive analog-to-digital conversion is illustrated.

[0073] Magnetic field B x The nth analog-to-digital conversion is at T nThe processor 36 analyzes subsequent samples of the digital sensor signal at the output of the ADC 32 and determines low signal strength (low SNR) and low or zero signal dynamics (e.g., variance or standard deviation). Therefore, the processor 36 sets the conversion time to 4T in this example. s (e.g. 4 samples for averaging). Magnetic field B x The (n+1)th analog-to-digital conversion is at T n+1 The processor 36 analyzes one or more subsequent samples of the digital sensor signal at the output of the ADC 32 and determines a slightly higher signal strength (SNR) and slightly higher signal dynamics (e.g., variance or standard deviation) than Tn. Thus, in this example the processor 36 reduces the conversion time from 4T to s (ie 4 samples) is reduced to T s (i.e. 1 sample). Magnetic field B x The (n+2)th analog-to-digital conversion is at T n+2 Processor 36 analyzes one or more subsequent samples of the digital sensor signal at the output of ADC 32 and determines whether the signal is related to T n+1 Compared to higher signal strength (SNR) and higher signal dynamics (such as variance or standard deviation). Therefore, in this example, processor 36 maintains the conversion time at T s Magnetic field B x The (n+2)th analog-to-digital conversion is at T n+3 Processor 36 analyzes one or more subsequent samples of the digital sensor signal at the output of ADC 32 and determines whether the signal is related to T n+2 Compared to high signal strength (SNR) but low or zero signal dynamics (eg variance or standard deviation). Due to the high signal strength (SNR), in this example the processor 36 keeps the switching time T low s (i.e. 1 sample). Magnetic field B x The (n+4)th analog-to-digital conversion is at T n+4 Processor 36 analyzes one or more subsequent samples of the digital sensor signal at the output of ADC 32 and determines whether the signal is related to T n+3 Due to the high signal dynamics, the processor 36 keeps the switching time T low in this example. s (i.e. 1 sample). Magnetic field B x The (n+5)th analog-to-digital conversion is at T n+5 Processor 36 analyzes one or more subsequent samples of the digital sensor signal at the output of ADC 32 and determines relative to T n+4Due to the low signal strength (SNR) and low signal dynamics (e.g., variance or standard deviation), the processor 36 can increase the conversion time to 4T in this example. s (ie 4 samples). The skilled person will appreciate that other switching times may also be possible.

[0074] Embodiments of the present disclosure propose adaptation of the measurement length. The use of average noise can adapt to the needs of SNR and thus reduce current consumption over time. The inputs for the algorithm can be signal strength and the dynamics of the signal.

[0075] The aspects and features described with respect to a specific example of the aforementioned examples may also be combined with one or more other examples to replace equivalent or similar features of the other examples, or to additionally introduce features into the other examples.

[0076] The example may further be or relate to a (computer) program, which includes a program code that performs one or more of the above methods when the program is executed on a computer, a processor or other programmable hardware component. Therefore, the steps, operations or processes of the different methods described above can also be performed by a programmed computer, a processor or other programmable hardware component. The example may also cover a program storage device (such as a digital data storage medium), which is readable by a machine, a processor or a computer, and encodes and / or contains programs and instructions that are executable by a machine, a processor or a computer. For example, the program storage device may include or may be a digital storage device, a magnetic storage medium (such as a disk and a tape), a hard drive or an optically readable digital data storage medium. Other examples may also include a computer, a processor, a control unit, a (field) programmable logic array ((F)PLA), a (field) programmable gate array ((F)PGA), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), an integrated circuit (IC) or a system on a chip (SoC) that is programmed to perform the steps of the above method.

[0077] It is further understood that, unless expressly stated in individual cases or necessary for technical reasons, the disclosure of several steps, processes, operations or functions disclosed in the specification or claims should not be interpreted as implying that these operations must depend on the described order. Therefore, the foregoing description does not limit the execution of several steps or functions to a certain order. In addition, in other examples, a single step, function, process or operation may include and / or be decomposed into several sub-steps, sub-functions, sub-processes or sub-operations.

[0078] If some aspects have been described with respect to a device or system, these aspects should also be understood as descriptions of corresponding methods. For example, a block, device, or functional aspect of a device or system may correspond to a feature (such as a method step) of a corresponding method. Therefore, aspects described with respect to a method should also be understood as descriptions of corresponding blocks, corresponding elements, attributes, or functional features of a corresponding device or corresponding system.

[0079] The following claims are hereby incorporated into the detailed description, where each claim may stand on its own as a separate example. It should also be noted that, although in the claims, a dependent claim refers to a specific combination with one or more other claims, other examples may also include combinations of dependent claims with the subject matter of other dependent claims or independent claims. Unless it is stated in individual cases that a specific combination is not intended, such a combination is hereby explicitly proposed. In addition, features of a claim should also be included with respect to any other independent claim, even if the claim is not directly defined as dependent on the other independent claim.

Claims

1. An analog-to-digital conversion ADC circuit (30) for sensor signals, comprising: An input interface (31) configured to receive an analog sensor signal; an analog-to-digital converter (32) configured to digitize the analog sensor signal to obtain samples of a digital sensor signal; a digital filter (34) configured to average a number of samples of the digital sensor signal to obtain an average sensor signal; A processor (36) configured to adjust the number of samples averaged to obtain the average sensor signal based on one or more characteristics of the analog sensor signal or the digital sensor signal; as well as An output interface (38) for said average sensor signal.

2. The ADC circuit (30) according to claim 1, wherein the characteristic of the analog sensor signal or the digital sensor signal comprises a signal strength and / or a signal dynamics of the analog sensor signal or the digital sensor signal.

3. The ADC circuit (30) of any one of the preceding claims, wherein the processor (36) is configured to determine a signal strength of the analog sensor signal or the digital sensor signal and to adjust the number of averaged samples based on the signal strength.

4. The ADC circuit (30) of claim 3, wherein the processor is configured to decrease the number of averaged samples if the signal strength increases and to increase the number of averaged samples if the signal strength decreases.

5. The ADC circuit (30) of claim 3 or 4, wherein the processor (36) is configured to compare the signal strength to one or more predefined thresholds and select the number of averaged samples based on the comparison.

6. An ADC circuit (30) according to any of the preceding claims, wherein the processor (36) is configured to determine a signal dynamic of the analog sensor signal or the digital sensor signal and to adjust the number of averaged samples used to obtain the average sensor signal based on the signal dynamics.

7. The ADC circuit (30) of claim 6, wherein the processor (36) is configured to reduce the number of averaged samples if the signal dynamically increases, and to increase the number of averaged samples if the signal dynamically decreases.

8. The ADC circuit (30) of claim 6 or 7, wherein the processor (36) is configured to compare the signal dynamics to one or more predefined thresholds and select the number of averaged samples based on the comparison.

9. The ADC circuit (30) according to any one of the preceding claims, further comprising a selector, which is configured to select one or more characteristics of the analog sensor signal or the digital sensor signal, and adjust the number of averaged samples based on the one or more characteristics.

10. The ADC circuit (30) according to any one of the preceding claims, wherein the analog-to-digital converter (32) comprises a ΣΔ-ADC.

11. The ADC circuit (30) according to any one of the preceding claims, further comprising: Magnetic field sensor (10; 40), coupled to the input interface to provide an analog magnetic field sensor signal.

12. The ADC circuit (30) of claim 11, wherein the magnetic field sensor (10; 40) comprises a 3D Hall sensor.

13. A method for analog-to-digital conversion of a sensor signal, the method comprising: Receive analog sensor signals; digitizing the analog sensor signal to obtain samples of a digital sensor signal; averaging a number of samples of the digital sensor signal to obtain an average sensor signal; adjusting the number of samples averaged based on one or more characteristics of the analog sensor signal or the digital sensor signal to obtain the average sensor signal; as well as The average sensor signal is output.

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