Dynamic integration time controller for time-of-flight ranging systems

Abstract

The present disclosure relates to a dynamic integration time controller for time-of-flight ranging systems. According to embodiments, a system can dynamically control the integration time in a time-of-flight (ToF) device based on the current operating state. A signal scaler processes calibration data and real-time measurements to determine the desired signal and ambient rate. Parallel calculations determine the desired integration time, one based on achieving maximum ranging distance and the other based on the measurement accuracy requirements. The system selects the longer integration time and applies user-defined bounds to optimize power consumption while maintaining specified performance. By adapting the integration time to ambient light conditions and target reflectivity characteristics, the system is able to shorten the integration time in favorable conditions while automatically increasing the duration when needed for long distances or low reflectivity targets.

Description

Technical Field

[0001] This disclosure generally relates to time-of-flight ranging systems, and in certain embodiments, to dynamic control of integration time in a time-of-flight device. Background Technology

[0002] Distance measurement systems have utilized a variety of techniques, from ultrasonic to optical methods. Among optical measurement techniques, the time-of-flight (ToF) method uses high-speed light pulses to accurately determine distance.

[0003] Advances in semiconductor technology have enabled the development of specialized light sources, such as vertical-cavity surface-emitting lasers (VCSELs). These sources can generate short-duration pulses with precise timing. Similarly, detector technology has evolved with devices such as single-photon avalanche diodes (SPADs), which are capable of detecting single photons with high temporal resolution.

[0004] Integration time represents a critical parameter in optical measurement systems. In photography, integration time determines exposure time. In scientific instruments, integration time affects measurement sensitivity and noise levels. A similar principle applies to distance measurement systems, where a longer integration period allows for greater signal accumulation.

[0005] Ambient light conditions have always posed a challenge to optical measurement systems. Natural and artificial lighting can introduce background photons that can affect measurements. Different applications face different levels of ambient light. For example, indoor industrial environments may have controlled lighting, while automotive applications may experience extreme variations in environmental conditions.

[0006] In optical measurements, the reflective properties of objects have long been considered. Materials can exhibit different reflective properties, ranging from diffuse to specular. Surface properties, color, and material composition can affect how much light returns to the detector.

[0007] Mobile and portable applications have driven advancements in power management techniques across many electronic systems. Battery-powered devices benefit from reduced power consumption while maintaining performance. Power optimization techniques have evolved from simple duty cycles to sophisticated adaptive control methods.

[0008] Signal processing in measurement systems has improved along with digital processing capabilities. Modern systems can perform complex real-time calculations, enabling sophisticated measurement data analysis. Digital processing can compensate for various measurement conditions and system non-ideals. Summary of the Invention

[0009] The technical advantages are generally realized through embodiments of this disclosure, which describe the dynamic control of integration time in a time-of-flight device.

[0010] The first aspect relates to a system for controlling integration time in a time-of-flight (ToF) device, the system comprising a signal scaler configured to receive calibration data and user input, and to calculate a desired signal rate and an ambient rate; a distance parameter calculator configured to calculate a first integration time based on the desired signal rate and the ambient rate; a sigma parameter calculator configured to calculate a second integration time based on the desired signal rate, the ambient rate, and a maximum sigma; and an integration time controller configured to select a desired integration time based on the first and second integration times, wherein the ToF device is configured to operate at the desired integration time.

[0011] The second aspect relates to a method for controlling integration time in a Time-of-Flight (ToF) device, the method comprising receiving calibration data and user input; calculating a desired signal rate and an ambient rate; calculating a first integration time based on a distance parameter using the desired signal rate and the ambient rate; calculating a second integration time based on a sigma parameter using the desired signal rate, the ambient rate, and a maximum sigma; selecting a desired integration time based on the first and second integration times; and configuring the ToF device to operate at the desired integration time.

[0012] The third aspect relates to a non-transitory computer-readable storage medium storing computer instructions for determining an integration time in a Time-of-Flight (ToF) device, the integration time, when executed by a processor, causing the processor to receive calibration data and user input; calculate a desired signal rate and an ambient rate; calculate a first integration time based on a distance parameter using the desired signal rate and the ambient rate; calculate a second integration time based on a sigma parameter using the desired signal rate, the ambient rate, and a maximum sigma; select a desired integration time based on the first and second integration times; and output the desired integration time for configuring the ToF device.

[0013] The implementation can be carried out in hardware, software, or any combination thereof. Attached Figure Description

[0014] To gain a more complete understanding of this disclosure and its advantages, reference is now made to the following description in conjunction with the accompanying drawings, wherein:

[0015] Figure 1 This is a block diagram of an embodiment of the integral time controller;

[0016] Figure 2 This is a block diagram of an embodiment of a signal scaler circuit;

[0017] Figure 3 This is a block diagram of the reciprocal distance calculator circuit in an embodiment;

[0018] Figure 4This is a block diagram of an embodiment of a reciprocal sigma calculator circuit;

[0019] Figure 5 This is a block diagram of the implementation's selection / restriction logic circuitry;

[0020] Figure 6 This is a flowchart of the method in the embodiment; and

[0021] Figure 7 This is a block diagram of the embodiment system. Detailed Implementation

[0022] This disclosure provides numerous applicable inventive concepts that can be implemented in a wide variety of specific contexts. Specific embodiments are merely illustrative of particular configurations and do not limit the scope of the claimed embodiments. Features from different embodiments may be combined to form other embodiments, unless otherwise indicated. Various embodiments are illustrated in the drawings, wherein identical parts and elements are indicated by the same reference numerals, and repeated descriptions are omitted for brevity.

[0023] The variations or modifications described in one embodiment may also be applied to other embodiments. Furthermore, various changes, substitutions, and alterations may be made without departing from the spirit and scope of this disclosure as defined by the appended claims.

[0024] While aspects of this disclosure have been described primarily in the context of time-of-flight ranging systems for autofocus (AF)-assisted, augmented reality / virtual reality (AR / VR) and proximity detection applications, it should be understood that these inventive aspects are also applicable to other applications. Specifically, aspects of this disclosure can be similarly applied to any ToF system in which power consumption optimization is required while maintaining specified ranging performance requirements, such as automotive sensing, consumer electronics, and industrial automation applications.

[0025] Time-of-Flight (ToF) devices measure distance by detecting reflected light pulses from an object. They can achieve a longer range and better measurement accuracy under low ambient light conditions compared to high ambient light conditions. Performance variations occur because ambient light introduces additional noise that affects the measurement.

[0026] In ToF devices, integration time represents the sampling time for each measurement. Longer integration times improve measurement quality but increase power consumption due to the longer device dwell time. Traditionally, ToF devices use a fixed integration time to ensure performance in worst-case scenarios, which wastes power under more favorable conditions.

[0027] Various aspects of this disclosure relate to dynamically adjusting the integration time based on current conditions and user requirements. In embodiments, the method begins with device calibration under known conditions, such as by measuring the signal strength of a target with known reflectivity at a known distance. The calibration data provides a reference point for calculating the desired integration time under different operating conditions. A signal scaling component adjusts the scaling measurement for different target reflectivities and distances.

[0028] In this embodiment, two parallel calculations determine the desired integration time. The first calculation determines the desired integration time to achieve a specified maximum ranging distance with minimal target reflectivity. The second calculation determines the desired integration time to achieve a specified measurement accuracy. The calculations account for the current ambient light level measured by the device. The controller can compare the calculated integration times and select a longer integration time to ensure performance requirements are met. The selected integration time can also be limited by user-specified minimum and maximum limits.

[0029] Therefore, in this embodiment, the device can use a shorter integration time under low-light conditions or when measuring nearby objects with high reflectivity, thereby reducing power consumption. The integration time can be automatically increased under bright conditions or when measuring distant or less reflective objects to maintain the specified performance. The calculation can be updated in each measurement frame (i.e., during operation) based on the current ambient light level. These and other details are further elaborated below.

[0030] Figure 1 This diagram illustrates an integration time controller 100 according to an embodiment of an aspect of this disclosure. The integration time controller 100 includes a signal scaler circuit 102, an inverse distance calculator circuit 104, an inverse sigma calculator circuit 106, and a selection / limiting logic circuit 108, which may (or may not) be arranged as shown. The integration time controller 100 may include additional components not shown.

[0031] Figure 1 An example of a dynamic integration time controller for a ToF device is shown. The process begins by calibrating the signal rate of each single-photon avalanche diode (SPAD) for a given target reflectivity and distance. For example, calibration can be performed using a target with 17% reflectivity at a distance of 400 mm.

[0032] The next step involves scaling the signal rate per SPAD based on the target reflectivity. This allows the system to determine the desired signal for a target with the minimum reflectivity at the same distance as calibration. For example, if the system is calibrated with a target that reflects 17% of the target's signal but needs to operate with a target that reflects 5% of the target's signal, the signal will be scaled by a factor of 5 / 17.

[0033] Next, the inverse square law of light propagation is used to scale the signal rate per SPAD for the desired maximum distance. For example, if calibration is performed at 400mm, but the system needs to operate at a maximum distance of 1600mm, then the signal rate will be factored out as the light intensity decreases with the square of the distance. Scaling.

[0034] Given the signal rate at the desired maximum distance, the system calculates the integration time required to achieve target detection above the ambient noise floor. This calculation takes into account the ambient noise floor and scales from the current reflectivity estimate based on the current ambient rate and the desired minimum reflectivity.

[0035] The system determines the integration time to achieve a specified range standard deviation by using the signal rate calculated at the desired maximum distance. The calculation takes into account the desired signal and ambient light level of the target with the desired minimum reflectivity at the desired maximum distance.

[0036] The process allows ToF devices to dynamically adjust the integration time based on current conditions, optimizing power consumption while maintaining the desired performance specifications.

[0037] The signal scaler circuit 102 can receive user input, including minimum reflectivity (REF), maximum sigma, minimum value of maximum ranging distance (DMAX) (MIN), minimum integration time limit, and maximum integration time limit.

[0038] Minimum reflectance (REF) specifies the percentage of light reflected from the target object. In this embodiment, the minimum reflectance (REF) is set to 54%. Maximum sigma specifies the standard deviation in distance measurement. Maximum ranging distance (DMAX) is the farthest distance at which the ToF device can detect a target with a specified minimum reflectance (REF). The minimum and maximum integration time limits are the lower and upper limits of the integration time used for measurement rate control.

[0039] The signal scaler circuit 102 can also receive calibration data, such as calibration distance (D). CAL ), signal strength at calibration distance (SD) CAL ) and reflectance at calibration (REFD) CAL Calibration distance (D) CAL The distance is the reference distance for initial calibration measurements. The signal strength (SD) at the calibration distance... CAL The peak signal rate is the measured value at a calibration distance for a target with known reflectivity. In this embodiment, the calibration distance (SD) is... CAL The signal strength at that location is provided as events per second per SPAD (event / s.SPAD). Reflectivity at calibration (REFD) CAL () is the percentage of the reflectance of the target used during calibration.

[0040] The calibration process sets the integration time controller 100 for optimal performance. In this embodiment, the signal strength is measured at a known distance from a target with known reflectivity. For example, a target with 17% reflectivity at a distance of 400 mm can be used to perform the calibration. These specific values ​​are chosen because they represent typical conditions for many applications, although different values ​​can be used to calibrate the system if required for a particular use case.

[0041] The system measures the peak signal rate at the calibration distance during calibration. This measurement is typically provided in events per SPAD (single-photon avalanche diode) per second. Calibration data includes the calibration distance (D... CAL ), signal strength at calibration distance (SD) CAL ) and reflectance at calibration (REFD) CAL (This can be stored and used as a reference point for subsequent calculations).

[0042] The calibration process allows the system to establish a baseline for signal strength under known conditions. This baseline is then used for scaling calculations for different target reflectivities and distances during operation. By starting from a known reference point, the system can more accurately estimate signal strength and desired integration time for various real-world scenarios.

[0043] The system can dynamically adjust the integration time using calibration data and real-time measurements. Combining pre-calibration data and real-time measurements allows the system to adapt to changing conditions while maintaining a reliable reference point.

[0044] The signal scaler circuit 102 can receive real-time measurements from the current target, including ambient light level (current environment) and reflectivity estimate (current reference). In this embodiment, the ambient light level is provided as events per second per SPAD.

[0045] The signal scaler circuit 102 can also receive pulse start and end parameters from the pulse divider. These typically define static configuration parameters that are optimized for finding a given pulse from the detector during device characterization. The pulse divider parameters affect how the signal and ambient rates are scaled for reciprocal calculations.

[0046] The signal scaler circuit 102 scales these inputs based on the relationship between calibration conditions and desired operating conditions, taking into account differences in target reflectivity, pulse divider configuration, and the inverse square law of distance.

[0047] The scaled output may include the desired signal rate at the maximum ranging distance for the desired minimum reflectivity and the expected ambient rate at the maximum ranging distance, incorporated into the pulse divider parameters in the calculation. These scaled values ​​are provided as input to the reciprocal distance calculator circuit 104 and the reciprocal sigma calculator circuit 106.

[0048] Despite Figure 1 It is not shown as a separate component, but the pulse divider works as part of the ToF sensor system, working in conjunction with the signal scaler circuit 102 to optimize the detection and processing of light pulses.

[0049] The pulse divider defines static configuration parameters for identifying and analyzing the light pulses returned from the detector. These parameters can be optimized during device characterization to ensure the system can effectively locate and measure relevant portions of the returned signal. Specifically, the pulse start and end parameters help define the time window in which the system expects to receive the reflected light pulses.

[0050] With the integral time controller 100, the pulse divider parameters affect how the signal and ambient rates are scaled for the reciprocal calculation. By defining pulse boundaries, the pulse divider helps to separate the actual signal from background noise and ambient light, thereby improving the accuracy of subsequent calculations.

[0051] The integration time controller 100 receives pulse divider parameters as input, allowing it to adjust its calculations based on the specific pulse characteristics used. Integration ensures that dynamic adjustments to the integration time are made with a full understanding of how the light pulses are emitted and detected, resulting in more accurate and efficient operation of the ToF device.

[0052] It is important to note that while the pulse divider parameters are typically static and set during device characterization, they play a dynamic role in the ongoing calculations performed by the integral time controller. By combining these parameters, the system can maintain optimal performance under a variety of operating conditions and measurement scenarios.

[0053] The reciprocal distance calculator circuit 104 receives scaled signal rate and ambient rate from the signal scaler circuit 102. Using these inputs, a first integration time is calculated based on a minimum distance requirement. This calculation may take into account signal confidence levels and ambient noise basis assumptions consistent with histogram processing requirements.

[0054] The reciprocal sigma calculator circuit 106 receives precise scaling and ambient rate from the signal scaler circuit 102. Using these inputs and the maximum sigma specification, the reciprocal sigma calculator circuit 106 can calculate the second integration time based on accuracy requirements. This calculation can be combined with pulse width parameters and bin width settings from the ToF device.

[0055] The selection / limiting logic circuit 108 receives the calculated integration times from the reciprocal distance calculator circuit 104 and the reciprocal sigma calculator circuit 106. It compares them to determine which requirement might be more restrictive. When the sigma-based integration time exceeds the distance-based integration time, the selection / limiting logic circuit 108 can select a sigma-based value and set a limit flag. The selection / limiting logic circuit 108 can ensure that the selected integration time falls within specified minimum and maximum limits before outputting the final desired integration time value.

[0056] The integrated time controller 100 is configured to dynamically adjust the integration time of the host device to the minimum value desired to achieve a specified performance metric, thereby minimizing power consumption while maintaining the desired ranging capability. Dynamic adjustment is advantageous when ambient light conditions or target reflectivity change, allowing the device to adapt to changing environmental conditions in real time.

[0057] The integration time controller 100 can calculate the optimal integration time to satisfy user-specified parameters such as target reflectivity, maximum ranging distance, and desired range accuracy (σ, sigma). Compared to static or simplified methods, this method allows for more granular and efficient control of the ToF device. For example, the dynamic system continuously optimizes the device's operation instead of using a fixed integration time, which might waste power under favorable conditions or fail to meet performance requirements in challenging environments.

[0058] The Integral Time Controller 100 balances power consumption, the trade-off between ranging distance and measurement accuracy, and ensures that ToF devices operate at peak efficiency over a wide range of conditions.

[0059] Figure 2 A block diagram of an embodiment of a signal scaler circuit 200, which can be implemented as a signal scaler circuit 102, is shown. The signal scaler circuit 200 includes a first scaling circuit 202, a second scaling circuit 204, a third scaling circuit 206, a fourth scaling circuit 208, a fifth scaling circuit 210, a first multiplier circuit 212, a second multiplier circuit 214, a third multiplier circuit 216, a fourth multiplier circuit 218, a fifth multiplier circuit 220, a sixth multiplier circuit 222, a seventh multiplier circuit 224, a summing circuit 226, and a dynamic signal scaling (DSS) circuit 228, which may (or may not) be arranged as shown. The signal scaler circuit 200 may include additional components not shown.

[0060] The signal scaler circuit 200 is configured to process various inputs to generate a scaled output for subsequent calculations. The circuit receives multiple inputs from the ToF device, including calibration data, user-specified parameters, and current measurements.

[0061] The signal scaler circuit 200 begins by processing the ambient light level through a series of scaling operations. First, it applies a scaling factor equal to the ratio of the minimum to the current reflectance estimate. The scaled ambient signal is normalized by converting the per-SPAD rate to a per-cell rate by dividing the scaled ambient signal by the number of histogram cells used in the ToF device.

[0062] Furthermore, the circuit processes the signal strength at the calibration distance. It scales the value using the ratio between the minimum reflectivity and the reflectivity at calibration. The resulting value is further scaled using the ratio between the square of the calibration distance and the square of the maximum ranging distance, based on the inverse square law of light propagation. This process illustrates the signal strength difference between the calibration distance and the desired maximum ranging distance.

[0063] Then, the signal scaler circuit 200 combines the distance scaling signal with the scaled ambient signal. The combined signal is processed by incorporating a safety factor and target rate specific to the ToF device to generate an effective SPAD scaling value.

[0064] The final outputs of the signal scaler circuit are an ambient output signal and a desired signal rate. The ambient output signal represents the expected ambient rate at the maximum ranging distance for a target with minimum reflectivity. The desired signal rate represents the desired signal rate at the maximum ranging distance for a target with minimum reflectivity. In this embodiment, these outputs are provided in events per second per bin.

[0065] By performing a scaling operation, the signal scaler circuit 200 adapts the calibration measurements to the current operating conditions, thus taking into account differences in reflectivity, distance, and ambient light level. These scaled outputs are used in subsequent calculations performed by the reciprocal distance calculator and reciprocal sigma calculator circuits.

[0066] Signal scaling circuit 200 processes the ambient light level (current environment) through a series of scaling operations. First scaling ratio circuit 202 uses, for example, a reflectance estimator to provide a first scaling factor equal to the ratio between the minimum reflectance (reference, REF) and the reflectance estimate (current reference). First multiplier circuit 212 scales the ambient light level using the first scaling factor provided by the first scaling ratio circuit 202 to provide a scaled ambient signal.

[0067] The reflectivity estimation process provides real-time input for ambient light scaling calculations. The system can continuously estimate the reflectivity of the measured current target, allowing it to scale the ambient light signal by the ratio of calibrated reflectivity to desired reflectivity.

[0068] exist Figure 2Not explicitly shown, but fed to the signal scaler circuit 200, the reflectivity estimator uses data from the ToF sensor to approximate the reflectivity of the target object. The estimation can be based on the strength of the returned signal relative to the transmitted signal, taking into account factors such as known transmitted power and the measured distance to the target. As the sensor moves from one target to another with different reflectivity characteristics, the reflectivity estimator provides continuous updates to maintain accurate ambient light scaling.

[0069] By providing the desired ratio of the scaled ambient light signal based on the difference between the calibrated and actual target reflectivity, the reflectivity estimation process enables appropriate ambient light scaling across a wide range of target materials.

[0070] The second scaling circuit 204 provides a value equal to the reciprocal of the number of histogram bins (i.e., The second scaling factor is used to normalize the output of the first multiplier circuit 212. The second multiplier circuit 214 normalizes the output of the first multiplier circuit 212 by using the second scaling factor provided by the second scaling circuit 204. The second multiplier circuit 214 converts the per-SPAD rate to the per-cell rate.

[0071] The third scaling circuit 206 provides a third scaling factor, which is equal to the minimum reflectivity (REF) and the reflectivity during scaling (REF_D). CAL The ratio between ) . The fourth multiplier circuit 218 uses the third scaling factor (i.e., provided by the third scaling circuit 206) ) to scale the calibration distance (SD) CAL The signal strength at ().

[0072] The fourth scaling circuit 208 provides a fourth scaling factor, which is equal to the calibration distance (D). CAL The ratio of the square of the distance to be measured to the square of the maximum distance to be measured (DMAX). This ratio is determined by the inverse square law of light. For example, if calibrated at 400mm but measured at 1600mm, the signal is reduced by 1 / 16. Because light intensity decreases with the square of the distance. The fifth multiplier circuit 220 uses the fourth scaling factor (i.e., provided by the fourth scaling circuit 208) to... The output of the fourth multiplier circuit 218 is scaled to provide a distance-scaled signal at the output of the fifth multiplier circuit 220.

[0073] Summing circuit 226 combines the range-scaled signal with the scaled ambient signal (output of first multiplier circuit 212) to provide input to DSS circuit 228. DSS circuit 228 processes the combined signal to produce an effective SPAD scaling value, which incorporates the safety factor of the ToF device and the target rate. Third multiplier circuit 216 multiplies the effective SPAD value by the scaling result from second multiplier circuit 214 to produce an ambient output signal (ambient). The ambient output signal is the distance-scaled signal at the maximum ranging distance (D) for a target with minimum reflectivity (reference, REF). MAX The expected environmental rate at ) is specified. In this embodiment, the environmental output signal is provided as events per second per bin (events / s.bin).

[0074] U.S. Patent Application No. 15 / 709,791, entitled "Circuit and Method for Controlling a SPADArray," owned by the same assignee, is incorporated herein by reference in its entirety. The incorporated application discloses a Dynamic Signal Scaling (DSS) method for controlling the event rate of a SPAD array. Specifically, the DSS enables and disables individual SPADs to maintain a combined event rate at the OR tree, wherein events from individual SPADs are logically ORed together below a predetermined threshold. The threshold can be set using a safety factor relative to the theoretical maximum OR tree rate. For example, a safety factor of ten (i.e., 10) keeps the event rate below one-tenth of the theoretical maximum OR tree rate. This safety margin helps prevent nonlinearity in range measurements when the total peak rate, including signal and ambient events, approaches the maximum rate capability of the OR tree.

[0075] Similar to the second scaling circuit 204, the fifth scaling circuit 210 provides a value equal to the reciprocal of the number of histogram bins (i.e., The fifth scaling factor is used to normalize the distance scaling signal at the output of the fifth multiplier circuit 220 using the fifth scaling factor provided by the fifth scaling circuit 210. The sixth multiplier circuit 222 converts the per-SPAD rate to a per-bin rate.

[0076] The number of histogram bins can affect how a ToF device processes and analyzes the returned optical signal. In the signal scaler circuit 200, the second scaling circuit 204 and the fifth scaling circuit 210 provide a scaling factor equal to the reciprocal of the number of histogram bins. The scaling operation performed by the second multiplier circuit 214 and the sixth multiplier circuit 222 converts the per-SPAD rate to a per-bin rate. This conversion may be necessary because the raw data from the ToF sensor is typically collected on a per-SPAD basis, but subsequent processing and analysis are often performed more efficiently on a per-bin basis.

[0077] The number of histogram bins can vary depending on specific equipment configurations and requirements. Typical values ​​may include 32, 64, or 128 bins, but other values ​​are also possible. The choice of bin count affects the temporal resolution of the measurement and the computational complexity of signal processing.

[0078] Cellar normalization is advantageous because it allows the system to operate on a consistent unit throughout the computation. By normalizing the signal to the basis of each cell, the system can more accurately compare and combine different measurements, regardless of the specific SPAD array configuration or the number of SPADs activated during a given measurement.

[0079] Furthermore, using histogram bins helps manage the trade-off between measurement accuracy and processing efficiency. A greater number of bins can provide finer temporal resolution but may require more computational resources, while fewer bins can accelerate processing at the cost of some accuracy. The integration time controller 100 can be configured to operate effectively across different bin configurations, adapting its calculations to the specific histogram structure used.

[0080] It is worth noting that the bin width, which is related to the number of bins and the total measurement window, also affects the accuracy of the ToF measurement. When performing its calculations, the system can take this into account to ensure that the integration time adjustment is suitable for the time resolution provided by the selected bin configuration.

[0081] The seventh multiplier circuit 224 applies the effective SPAD scaling value from the DSS circuit 228 to the output of the sixth multiplier circuit 222 to target the target with minimum reflectivity (REF) at the maximum ranging distance (D). MAX The desired signal rate (SD) is generated at ) MAX In the embodiment, the desired signal rate (SD) MAX The events are provided per second per warehouse (events / s.warehouse).

[0082] Therefore, the signal scaler circuit 200 produces two outputs: an ambient output signal representing the scaled ambient light rate, and a desired signal rate representing the desired signal rate at the maximum ranging distance. The scaling values ​​include adjustments for reflectivity difference, distance scaling according to the inverse square law, histogram bin normalization, and an effective SPAD scaling factor. The reciprocal distance calculator circuit 104 and the reciprocal sigma calculator circuit 106 use the scaled output from the signal scaler circuit 200 to determine their respective integration times, thereby effectively adapting the calibration measurement to the current operating conditions.

[0083] Figure 3This diagram illustrates an embodiment of a reciprocal distance calculator circuit 300, which can be implemented as a reciprocal distance calculator circuit 104. The reciprocal distance calculator circuit 300 includes a first square root circuit 302, a second square root circuit 304, a first multiplier circuit 306, a second multiplier circuit 308, a summation circuit 310, a division circuit 312, and an exponentiation circuit 314, which may (or may not) be arranged as shown. The reciprocal distance calculator circuit 300 may include additional components not shown.

[0084] The reciprocal distance calculator circuit 300 is configured to calculate the reciprocal distance integration time based on input from a signal scaler circuit. The circuit receives the ambient output signal and the desired signal rate at the maximum ranging distance, both provided in events per second per compartment.

[0085] The reciprocal distance calculator circuit 300 includes two parameters to ensure performance accuracy: the signal confidence value and the ambient noise floor. In one embodiment, the signal confidence value is set to a default value of 3 / √16 to evaluate the reliability of the signal return under different conditions. The ambient noise floor is set to a default value of 7 / √16 in one embodiment, allowing the circuit to adjust for noise variations that may affect the distance measurement.

[0086] The circuit begins its calculations with two square root operations. The first square root circuit processes the ambient output signal, while the second square root circuit processes the desired signal rate. The square root values ​​are then multiplied by the ambient noise floor and the signal confidence value, respectively.

[0087] The outputs of the multiplication are summed. The sum is then divided by the desired signal rate. The final step involves squaring the result of the division.

[0088] The circuit outputs a reciprocal distance integration time in seconds. Taking into account current environmental conditions and desired signal strength, this value represents the expected integration time to achieve the specified maximum ranging distance under minimum target reflectivity.

[0089] By performing these calculations, the reciprocal distance calculator circuit 300 ensures that the ToF device can maintain optimal performance while adapting to changing environmental conditions in real time. The resulting integration time balances the need for accurate distance measurement with the goal of minimizing power consumption.

[0090] In this embodiment, the reciprocal distance calculator circuit 300 is configured to use the ambient output signal and the maximum ranging distance (D) provided by the signal scaler circuit 200. MAX The reciprocal distance integral time (ID) is calculated using the expected signal rate at ( ). MAX These inputs can be calculated as events per second per bin, allowing the system to account for changes in ambient light conditions and the desired signal return.

[0091] In this embodiment, the reciprocal distance calculator circuit 300 is configured to consider the signal confidence value (SCONF) and the ambient noise floor (ACONF) to ensure performance accuracy. These components enable the circuit to dynamically determine the reciprocal distance (ID). MAX ).

[0092] The signal confidence value is used to assess the reliability of signal return in different scenarios, consistent with the effective range assumption of photon return signal (PRS).

[0093] The ambient noise baseline parameter allows the circuit to adjust for noise variations that may affect the ranging measurement. It reflects the environmental conditions processed through the histogram assumption.

[0094] The reciprocal distance calculator circuit 300 ensures that the calculated distance is aligned with current environmental and device-specific variables by taking into account signal confidence and environmental noise factors. This integration allows the ToF device to maintain optimal performance while adapting to changing conditions in real time.

[0095] To obtain the time (ID) used for reciprocal distance integration MAX The equations relating to U.S. Patent Nos. 11,120,104, 11,797,645 and 18 / 466,522 are jointly owned by the same assignees as this disclosure, and the entire contents of which are incorporated herein by reference.

[0096] In these references, the maximum ranging distance (D) MAX ) Calculate the maximum ranging distance used to design the current environmental conditions under a specific target reflectivity. Here, the maximum ranging distance is specified as an input with the target reflectivity to determine the integration time.

[0097] Therefore, as derived from U.S. Patent Nos. 11,120,104, 11,797,645, and 18 / 466,522: And the desired signal rate (SD) MAX Substituting the integral time (I) into the equation, we can obtain:

[0098] When divided by the square root and the reciprocal distances rearranged, the following equation is obtained:

[0099] Figure 3 An example implementation of a reciprocal distance calculator circuit 300 for calculating the reciprocal distance equation is shown.

[0100] The first square root circuit 302 receives the ambient output signal (AMBIENT) from the signal scaler circuit 200 as input and generates the corresponding square root value. The square root value It is reached by multiplying the first multiplier circuit 306 with the ambient noise floor (ACONF).

[0101] The second square root circuit 304 receives the desired signal rate (SD) from the signal amplification circuit 200. MAX It takes as input and generates the corresponding square root value. The square root value is obtained by multiplying the signal confidence value (SCONF) by the second multiplier circuit 308. .

[0102] The summing circuit 310 receives the outputs of the first multiplier circuit 306 and the second multiplier circuit 308 as inputs, and combines them to reach... .

[0103] The division circuit 312 receives the output of the summing circuit 310 and the desired signal rate (SD) from the signal amplification circuit 200. MAX It takes as input. It performs a division operation to reach . .

[0104] Finally, the exponent circuit 314 calculates the square of the value provided by the division circuit 312 to obtain the square of the value. The squared value is provided as the reciprocal distance integral time (ID) at the output of the reciprocal distance calculation circuit 300. MAX In this embodiment, the reciprocal distance integration time (ID) is provided in seconds. MAX ).

[0105] Figure 4 This diagram illustrates an embodiment of a reciprocal sigma calculator circuit 400, which can be implemented as a reciprocal sigma calculator circuit 106. The reciprocal sigma calculator circuit 400 includes a first multiplier circuit 402, a first divider circuit 404, a first exponentiation circuit 406, a second multiplier circuit 408, a summation circuit 410, a subtraction circuit 412, a third multiplier circuit 414, a second exponentiation circuit 416, a fourth multiplier circuit 418, and a second divider circuit 420, which may (or may not) be arranged as shown. The reciprocal distance calculator circuit 300 may include additional components not shown. The reciprocal sigma calculator circuit 400 processes the input through multiple stages to calculate the integration time desired to achieve a specified measurement accuracy.

[0106] In U.S. Patent Nos. 11,120,104, 11,797,645, and 18 / 466,522, sigma estimators are used to estimate the sigma of distance measurement noise and distance output. Here, the desired sigma is specified as the input to the computation integration time.

[0107] Assuming the phase-weighted filtered histogram comprises a first part (A), a second part (B), and a third part (C), the phase sigma calculation equation disclosed in the aforementioned patents and applications can be derived as follows: in It is the effective sigma phase and the width of the second part (B) in the phase-weighted filter histogram. It should be noted that the terms in the incorporated patents and applications can be ignored, as they involve crosstalk that is irrelevant in the context of maximum distance.

[0108] The phase-weighted filtering histogram algorithm employs a specific positioning strategy for the first part (A), the second part (B), and the third part (C). The algorithm intentionally positions these parts to minimize the difference between the first part (A) and the third part (C) before calculating the final sub-cell phase, thereby achieving accurate distance measurement.

[0109] The relationship between Part A and Part C can depend on the precise pulse shape and phase relative to the histogram bin. In some ranges, Part A and Part C will be exactly equal, although the specific range in which this occurs is usually a priori unknown before performing actual range measurements. Uncertainties may arise from the complex interaction between the pulse characteristics and the discrete nature of the histogram bin.

[0110] While perfect equality between the first part (A) and the third part (C) is not guaranteed across all ranges, the algorithm systematically minimizes their differences. This systematic minimization can result in small perturbations of the first part (A) and the third part (C) about zero, which provides the device with sub-library resolution. Therefore, assuming the algorithm works actively to minimize these differences, treating the first part (A) and the third part (C) as equal can be used as a reasonable approximation for integral-time computation.

[0111] The approximation simplifies sigma calculations while preserving the fundamental characteristics of the measurement system's accuracy. Small variations from the approximation can contribute to subcell resolution but do not significantly affect the determination of the total integration time.

[0112] Furthermore, the phase-weighted filtered histogram can be represented by rectangular pulses, the width of which is defined by the VCSEL pulse width (in bins) and the signal amplitude (in counts per bin). The histogram consists of three key regions (i.e., the first part (A), the second part (B), and the third part (C)), where the second part (B) has a bin width and represents the median bin of the pulse. Under optimal conditions, the pulse is centered such that its midpoint is aligned with the center of the second part (B), thus producing a symmetrical distribution on the histogram.

[0113] The symmetrical arrangement results in the number of counts in the first part (A) being equal to the number of counts in the third part (C). The total signal contribution can be expressed as the sum of the third part (C) and the first part (A), which is the total count in the pulse minus the count in the second part (B). The total value can be calculated by multiplying the sum of the signal in each compartment and the environment in each compartment by the difference between the pulse width and the width of the second part (B) (i.e., pulse width - BAV).

[0114] The phase sigma calculation utilizes the aforementioned relationship in its denominator, which is considered to be four times the square of the signal count in the second part (B) of the ambient light conditioning. Given the symmetry of the pulse distribution and the intentional alignment of the histogram regions, setting the first part (A) and the third part (C) to be equal provides a mathematical succinct simplification while preserving the fundamental characteristics of the phase measurement. This simplification leads to the final form of the phase sigma equation, which incorporates the contributions of both the signal and ambient light to accurately reflect the measurement precision.

[0115] By setting the first part (A) to be equal to the third part (C), the phase sigma calculation can be simplified to: It is equal to:

[0116] The system will have a desired signal rate (SD). MAX ) and the ambient output signal (AMBIENT) multiplied by the integration time ( This is used to convert the event rate into actual event counts. Therefore, the phase sigma equation can be expressed as:

[0117] .

[0118] The phase sigma equation represents the relationship between signal counts, environmental counts, and impulse characteristics. After incorporating the integration time to convert the rate to a count, the equation can be simplified by dividing the numerator and denominator by the integration time. This operation yields an expression for the phase sigma equation that includes the integration time as an input parameter:

[0119] However, the system requires a different approach. Instead of calculating the phase sigma equation for a given integration time, it needs to determine the integration time expected to achieve the desired sigma value. This equation can be solved by algebraically rearranging the reciprocal sigma integration time, making it an output parameter rather than an input.

[0120] The final transformation involves converting between measurement units. Although phase sigma is initially expressed in phases per unit, users typically specify the desired accuracy in millimeters. in It is the user-specified expected sigma of the target reflectivity in millimeters, and It is the width of a single histogram bin in a user-specified time unit (e.g., picosecond).

[0121] The system employs a conversion factor, utilizing the width of the second part (B) and the speed of light (constant 6.66 × 10⁻⁶). －12 (This is expressed as) the relationship between phase sigma and desired range accuracy in millimeters:

[0122] The first multiplier circuit 402 receives two inputs: a constant value of 6.66 × 10⁻⁶. －12 These values ​​are multiplied by the expected sigma (DESIRED_RTN_SIGMA) of the target reflectivity in millimeters. The output of this multiplication is fed into the first divider circuit 404, which divides the result by the width (BIN_WIDTH) of the individual histogram bins.

[0123] The first exponent circuit 406 processes the output from the first divide circuit 404, boosting the value to a second power to generate a scaling factor. The result is fed to the second multiplier circuit 408.

[0124] In parallel, the circuit processes the signal-dependent inputs through separate paths. The summing circuit 410 sums the inputs based on the desired signal rate (SD). MAX The summation circuit 410 is combined with the ambient signal (environment). The subtraction circuit 412 receives the pulse width (PULSE_WIDTH) and the width of the second part (B) as inputs, and subtracts the width of the second part (B) from the pulse width. The third multiplier circuit 414 multiplies the outputs from the summation circuit 410 and the subtraction circuit 412.

[0125] The second exponential circuit 416 processes the desired signal rate (SD) respectively. MAXThe input is 4. Its output is multiplied by a constant value of 4 by the fourth multiplier circuit 418. The results from the third multiplier circuit 414 and the fourth multiplier circuit 418 are fed to the second divider circuit 420, the output of which is coupled to the second multiplier circuit 408, where it is multiplied by the result from the first exponentiation circuit 406 to produce the reciprocal sigma integration time (I0). SIGMA ).

[0126] Through this series of mathematical operations, the reciprocal sigma calculator circuit 400 realizes the reciprocal sigma integration time equation, calculating the integration time required to achieve the desired measurement accuracy under the current operating conditions.

[0127] Figure 5 A block diagram is shown of an embodiment of selection / limitation logic circuit 500 that can be implemented as selection / limitation logic circuit 108. Selection / limitation logic circuit 500 includes a first comparator 502, a second comparator 504, and a third comparator 506, which may (or may not) be arranged as shown. Selection / limitation logic circuit 500 may include additional components not shown.

[0128] The selection / limiting logic circuit 500 is configured to select the reciprocal distance integration time (ID) provided by the reciprocal distance calculator circuit 104. MAX ) and the reciprocal sigma integration time (I) provided by the reciprocal sigma calculator circuit 106. SIGMA Choose the most conservative integration time between () and ().

[0129] The first comparator 502 receives the reciprocal distance integration time (ID) at its input. MAX ) and reciprocal sigma integration time (I SIGMA ). In response to the reciprocal sigma integral time (I) SIGMA The time is greater than the reciprocal distance integral (ID). MAX The integration time is set to the reciprocal sigma integration time (I). SIGMA Otherwise, the integration time is set to the reciprocal of the integration time (ID). MAX ).

[0130] In an embodiment, a flag is set (e.g., in a register) to indicate which of the two calculated integration times has been selected. For example, if the reciprocal sigma integration time (Ii) is selected... SIGMA If the reciprocal distance integration time (ID) is selected, then the flag can be set to 1. MAX If ), then the flag can be set to 0.

[0131] The second comparator 504 and the third comparator 506 provide a limiting function, wherein the selected integration time at the output of the first comparator 502 is compared with predetermined minimum and maximum limits. If the selected integration time exceeds these limits, the integration time is limited to an acceptable range.

[0132] In this embodiment, the second comparator 504 compares the selected integration time with the maximum integration time (I0). MAX The integration time is compared. If the selected integration time is greater than the maximum value, the integration time is set to the maximum value; otherwise, the integration time remains at the value of the selected integration time. In an embodiment, the maximum integration time is set to 15.5 milliseconds.

[0133] In this embodiment, the third comparator 506 compares the selected integration time with the minimum integration time (I0). MIN The selection is compared. If the chosen integration time is less than the minimum integration time, it is set to the minimum integration time; otherwise, it remains at the chosen integration time value. In this embodiment, the minimum integration time is set to 4 milliseconds.

[0134] The output of the third comparator 506 is provided as the integration time. In this embodiment, the integration time is provided in seconds.

[0135] Figure 6 A flowchart of an embodiment method 600 for dynamically determining the integration time of a ToF device to optimize power consumption and guarantee specified ranging performance is shown. In the embodiment, the integration time is dynamically adjusted based on environmental conditions, target reflectivity, or a combination thereof. Note that all steps outlined in the flowchart of the method are not necessarily required and may be optional. Furthermore, similarly, changes in the arrangement of steps, the removal of one or more steps and path connections, and the addition of steps and path connections are contemplated.

[0136] In step 602, calibration data and user input are received. The calibration data may include, for example, the calibration distance (D). CAL ), signal strength at calibration distance (SD) CAL ) and reflectance at calibration (REFD) CAL Parameters such as ) can be used. User input can include minimum reflectivity (REF), maximum sigma, and minimum maximum ranging distance (D). MAX ) and minimum and maximum integration time limits.

[0137] In step 604, a signal scaler circuit, for example, is used to calculate the desired signal and ambient rate. The signal scaler circuit processes inputs from calibration data, user specifications, and current measurements to produce a scaled output. It adjusts the calibrated signal strength based on the ratio between the desired minimum and the calibrated reflectivity. The circuit then scales this adjusted signal according to the inverse square law of distance, taking into account the difference between the calibrated distance and the desired maximum ranging distance.

[0138] The circuit scales the current environmental measurement of ambient light to account for the desired minimum reflectivity. Based on the number of histogram bins used in the device, the signal and environmental calculations are normalized to a per-interval rate.

[0139] The circuitry can also apply additional scaling factors to system-specific parameters, such as effective SPAD (single-photon avalanche diode) scaling. These calculations result in the desired signal rate and desired ambient rate at the maximum ranging distance for a target with a minimum specified reflectivity, thus providing crucial input for subsequent integration-time calculations.

[0140] In step 606, the first integration time is calculated based on the distance parameter using the desired signal and the ambient velocity. A reciprocal distance calculator circuit can perform the calculation, determining the desired integration time to achieve the specified maximum ranging distance with minimum target reflectivity.

[0141] The first integration time is primarily influenced by four key parameters: the ambient noise basis constant, the expected ambient velocity at the maximum ranging distance, the signal confidence constant, and the expected signal velocity at the maximum ranging distance. These parameters collectively illustrate the relationship between signal strength and ambient light level to achieve reliable distance measurement over a specified maximum range. The calculation balances the effects of ambient light interference and signal strength to ensure accurate distance detection while optimizing power consumption.

[0142] In step 608, the second integration time is calculated based on the desired signal rate, ambient rate, and a sigma parameter of the maximum sigma specified by the user. A reciprocal sigma calculator circuit can perform the calculation, which determines the integration time desired to achieve the specified measurement accuracy.

[0143] In step 610, a desired integration time is selected based on the first and second integration times. Typically, the longer of the two integration times is chosen to ensure that the distance and accuracy requirements are met.

[0144] In this embodiment, a flag indicates which integration time is selected. For example, if a second integration time (based on the sigma parameter) is selected, the flag can be set to 1; if a first integration time (based on the distance parameter) is selected, the flag can be set to 0. The flag can be used for diagnostic purposes or to inform subsequent processing steps about which parameter (distance or accuracy) currently limits the integration time.

[0145] The selected integration time is then limited between the minimum and maximum integration time limits specified by the user. This ensures that the integration time falls within the acceptable operating limits of the device.

[0146] In step 612, the ToF device is configured to operate using the determined desired integration time. This step may include updating device settings or parameters to achieve the new integration time. For the next measurement frame, the method may loop back to step 604, allowing for continuous adaptation to changing environmental conditions and ranging requirements.

[0147] Dynamic integration time controllers for ToF devices offer significant advantages, with power optimization being a key benefit. By dynamically adjusting the integration time based on current environmental conditions and target reflectivity, the system minimizes power consumption while maintaining specified ranging performance requirements.

[0148] The device can use a shorter integration time under low ambient light conditions or when measuring nearby highly reflective objects. This reduction in integration time directly translates to lower power consumption, as the device remains active for a shorter period during each measurement cycle. Conversely, the system automatically increases the integration time under bright conditions or when measuring distant or less reflective objects to maintain a specified performance level.

[0149] The adaptive approach contrasts with traditional ToF devices that use a fixed integration time. Such fixed-time systems are typically configured to ensure performance under worst-case conditions, often resulting in unnecessary power consumption when conditions are more favorable. The dynamic integration time controller eliminates this inefficiency by continuously optimizing the device's operation.

[0150] Furthermore, the proposed system allows users to specify their desired performance parameters, such as maximum ranging distance, minimum target reflectivity, and desired ranging accuracy. The method then satisfies these requirements while using the minimum necessary integration time. This user-configurable aspect enables power consumption optimization across a wide range of applications and use cases.

[0151] Power optimization through dynamic control is particularly advantageous for mobile and portable applications where battery life is a concern. By reducing power consumption without compromising performance, the system can extend the operating time of battery-powered devices, enhancing practicality and usability in a variety of fields such as augmented reality, automotive sensing, and industrial automation.

[0152] Overall, the power optimization advantages of this disclosure represent a significant advancement in technology, providing a more efficient and adaptable solution that balances performance requirements with energy savings.

[0153] While the proposed method provides a mathematically robust way to implement a dynamically adjusted integral-time controller, simplified mechanisms can be employed in certain applications. One such simplification involves using a lookup table of ambient signal levels for the integral time. This method represents the simplest implementation of the dynamic integral-time control concept.

[0154] However, it is important to note that while these simplification methods may be easier to implement, they will be suboptimal compared to the full algorithm approach. For example, lookup table methods may not account for all the nuances and variables considered in the full algorithm, potentially leading to less precise adjustments to the integration time.

[0155] Another alternative implementation could involve applying a similar approach to reduce the power of the vertical-cavity surface-emitting laser (VCSEL). However, this approach is generally less efficient and more challenging to implement in the types of ToF systems considered. This complexity arises from tuning the VCSEL power, which involves different trade-offs and considerations compared to tuning the integration time.

[0156] The alternative implementation highlights the flexibility of the overall concept of dynamic integral time control. While the full algorithmic approach offers a more accurate and adaptable solution, the simplified version is suitable for applications with limited computational resources or those that do not require the highest level of accuracy. The choice between the full algorithmic approach and the simplified alternative will depend on the specific requirements and constraints of the ToF system under discussion.

[0157] Figure 7 A block diagram of an embodiment system 700 is shown. System 700 includes a processor 702, a memory 704, a time-of-flight (ToF) sensor 706, a power supply unit (PSU) 708, and an interface 710, which may (or may not) be arranged as shown. Although in Figure 7 One of each (i.e., processor 702, memory 704, sensor 706, power supply unit 708, and interface 710) is shown, but the number of components is not limiting, and a greater number is similarly envisioned in other embodiments.

[0158] System 700 may include additional components not depicted, such as long-term memory (e.g., non-volatile memory, etc.), power management circuitry, security and encryption modules (e.g., Trusted Platform Module (TPM), etc.), Global Positioning Satellite (GPS) sensors, transmitters, receivers, cameras, etc. System 700 may be an electronic device, such as a smartphone, tablet computer, laptop computer, smartwatch, vehicle, or any system or subsystem capable of housing sensor 706.

[0159] In this embodiment, each component can communicate with any other component inside or outside the system 700. For example, each component can communicate using the I2C (Inter-Integrated Circuit) communication protocol, the I3C (Improved Inter-Integrated Circuit) communication protocol, the Serial Peripheral Interface (SPI) specification, etc. The I2C (Inter-Integrated Circuit) communication protocol can also be referred to as I2C or IIC.

[0160] Processor 702 can be any component or collection of components suitable for performing computational or other processing-related tasks. In embodiments, processor 702 is an application processor, a baseband processor, or a microcontroller.

[0161] Memory 704 can be any component or collection of components suitable for storing programs or instructions to be executed by processor 702. In one embodiment, memory 704 includes a non-transitory computer-readable medium. Memory 704 can store calibration data, user input, and measurement results.

[0162] The Time-of-Flight (ToF) sensor 706 measures the distance between itself and objects in its field of view by utilizing the speed of light. The ToF sensor 706 emits a light signal that propagates to the target object, is reflected from the target object, and is then captured by the ToF sensor 706. The time taken for this round trip is measured, and because the speed of light is constant, the distance to the object can be accurately calculated using this time measurement by the ToF sensor 706.

[0163] The ToF sensor 706 includes a light source 712, typically an infrared (IR) LED, a laser diode, or a vertical-cavity surface-emitting laser (VCSEL). The light source 712 emits a light signal toward the object to be measured. In one embodiment, the ToF sensor 706 uses continuous light waves (i.e., indirect time-of-flight (iToF)). In another embodiment, the ToF sensor 706 uses pulsed light signals (i.e., direct time-of-flight (dToF) applications).

[0164] At the signal receiving end is an array of photodetectors 714 sensitive to a specific wavelength of the emitted light. Sensor 706 may include a lens system 716 to focus the emitted light into a beam and ensure that reflected light is guided onto the array of photodetectors 714. In an embodiment, the photodetector array 714 is a single-photon avalanche diode (SPAD) detection array. The ToF sensor 706 may include additional components not shown, such as memory, a microcontroller, and a VCSEL driver.

[0165] The ToF sensor 706 may include a timing circuit 718 for precisely measuring the interval between the time of light emission and the time of light detection after reflection. In an embodiment, the timing circuit 718, together with the processor 702, provides signals to operate the sensor 706 (e.g., emitting light signals and receiving reflected light signals).

[0166] The integration time controller 100 is coupled to the processor 702, the light source 712, and the photodetector array 714. It receives input from the processor 702, including the current ambient light level and reflectance estimate. The integration time controller 100 can access calibration data and user input stored in the memory 704.

[0167] Based on these inputs, the integration time controller 100 calculates the optimal integration time for each measurement frame. The integration time controller 100 can adjust the operation of the light source 712 and the photodetector array 714 to achieve the calculated integration time.

[0168] Light source 712 emits light pulses according to the integration time set by integration time controller 100. These pulses are reflected by objects in the scene and returned to photodetector array 714. Photodetector array 714 operates for a duration specified by the integration time, capturing the returned light pulses.

[0169] Timing circuit 7168 measures the time between the emission and detection of light pulses and provides this information to processor 702. Processor 702 uses the timing data and a known integration time to calculate an accurate distance measurement.

[0170] In this embodiment, processor 702 receives data from ToF sensor 706, interprets the timing data, and converts it into a distance measurement. Processor 702 may apply algorithms to refine the data, compensating for factors such as ambient light noise or variations in object reflectivity to provide more reliable distance information. ToF sensor 706 may be a multi-area ToF sensor capable of measuring distances in multiple separate areas, such as 4×4, 8×8, or 16×16 areas.

[0171] The integration time controller 100 continuously updates the integration time for each measurement frame. It can increase the integration time under high ambient light conditions or when measuring distant or less reflective objects. Conversely, it can decrease the integration time under low light conditions or when measuring nearby or highly reflective objects.

[0172] Dynamic adjustment allows System 700 to maintain specified ranging performance while optimizing power consumption. System 700 can achieve longer ranging distances and better measurement accuracy under favorable conditions, while still meeting performance requirements in challenging environments.

[0173] The System 700 can be applied to a variety of applications, such as autofocus assistance, augmented reality / virtual reality, proximity detection, automotive sensing, and industrial automation. Dynamic integral time control enables the system to adapt to different ambient light conditions and object reflection characteristics encountered in these diverse applications.

[0174] In one embodiment, sensor 706 includes a dedicated processor embedded therein. In another embodiment, the dedicated processor embedded within sensor 706 executes some or all of the algorithms generally stated herein as being executed by processor 702. For the sake of brevity, the internal processor of the ToF sensor 706 is not described in detail.

[0175] The power supply unit 708 can be any component or collection of components that supplies power to one or more components within the system 700. The power supply unit 708 may include various power management circuits, charge storage components (i.e., batteries), etc.

[0176] Interface 710 can be any component or set of components that allows processor 702 to communicate with other devices / components or users. For example, interface 710 may be adapted to allow a user or sensor 706 to interact / communicate with system 700.

[0177] The first aspect relates to a system for controlling integration time in a time-of-flight (ToF) device, the system comprising a signal scaler configured to receive calibration data and user input, and to calculate a desired signal rate and an ambient rate; a distance parameter calculator configured to calculate a first integration time based on the desired signal rate and the ambient rate; a sigma parameter calculator configured to calculate a second integration time based on the desired signal rate, the ambient rate, and a maximum sigma; and an integration time controller configured to select a desired integration time based on the first and second integration times, wherein the ToF device is configured to operate at the desired integration time.

[0178] In a first implementation of the system, according to this first aspect, the calibration data includes a calibration distance, the signal strength at the calibration distance, and the reflectivity at the calibration point.

[0179] In a second implementation of the system, depending on the first aspect itself or any of the aforementioned implementations of the first aspect, the user input includes the minimum values ​​of minimum reflectivity, maximum sigma, and maximum ranging distance.

[0180] In a third implementation of the system, the signal scaler is further configured to adjust the desired signal rate based on the inverse square law of distance, depending on the first aspect itself or any of the aforementioned implementations of the first aspect.

[0181] In a fourth implementation of the system, according to the first aspect itself or any of the foregoing implementations of the first aspect, the distance parameter calculator is configured to calculate the first integration time based on the signal confidence value and the ambient noise basis.

[0182] In a fifth implementation of the system, according to the first aspect itself or any of the foregoing implementations of the first aspect, the sigma parameter calculator is configured to calculate the second integration time based on the pulse width and bin width of the ToF device.

[0183] In a sixth implementation of the system, according to the first aspect itself or any of the aforementioned implementations of the first aspect, the integration time controller is further configured to: set a flag indicating whether to select a first integration time or a second integration time; and limit the desired integration time between a minimum and a maximum integration time.

[0184] The second aspect relates to a method for controlling integration time in a Time-of-Flight (ToF) device, the method comprising receiving calibration data and user input; calculating a desired signal rate and an ambient rate; calculating a first integration time based on a distance parameter using the desired signal rate and the ambient rate; calculating a second integration time based on a sigma parameter using the desired signal rate, the ambient rate, and a maximum sigma; selecting a desired integration time based on the first and second integration times; and configuring the ToF device to operate at the desired integration time.

[0185] In a first implementation of the method, according to such a second aspect, the method further includes: updating the expected signal rate and ambient rate of each measurement frame of the ToF device.

[0186] In a second implementation of the method, calculating the desired signal rate, according to the second aspect itself or any of the foregoing implementations of the second aspect, includes scaling the calibrated signal strength based on the ratio between the desired minimum reflectivity and the calibrated reflectivity.

[0187] In a third implementation of the method, selecting the desired integration time, based on the second aspect itself or any of the aforementioned implementations of the second aspect, includes selecting the longer of the first integration time and the second integration time.

[0188] In a fourth implementation of the method, according to the second aspect itself or any of the foregoing implementations of the second aspect, the method further includes setting a flag to indicate whether the first integration time or the second integration time is selected as the desired integration time; and limiting the desired integration time between a minimum and a maximum integration time.

[0189] In a fifth implementation of the method, according to the second aspect itself or any of the foregoing implementations of the second aspect, the calibration data includes a calibration distance, the signal strength at the calibration distance, and the reflectivity at the calibration point.

[0190] In a sixth implementation of the method, depending on the second aspect itself or any of the aforementioned implementations of the second aspect, the user input includes the minimum values ​​of minimum reflectivity, maximum sigma, and maximum ranging distance.

[0191] The third aspect relates to a non-transitory computer-readable storage medium storing computer instructions for determining an integration time in a Time-of-Flight (ToF) device, the integration time, when executed by a processor, causing the processor to receive calibration data and user input; calculate a desired signal rate and an ambient rate; calculate a first integration time based on a distance parameter using the desired signal rate and the ambient rate; calculate a second integration time based on a sigma parameter using the desired signal rate, the ambient rate, and a maximum sigma; select a desired integration time based on the first and second integration times; and output the desired integration time for configuring the ToF device.

[0192] In a first implementation of the non-transitory computer-readable storage medium according to the third aspect of claim 15, the instructions further cause the processor to update the desired signal rate and ambient rate for each measurement frame of the ToF device.

[0193] In a second implementation of the non-transitory computer-readable storage medium, calculating the desired signal rate, according to the third aspect itself or any of the foregoing implementations of the third aspect, includes scaling the calibration signal strength based on the ratio between the desired minimum reflectivity and the calibration reflectivity.

[0194] In a third implementation of the non-transitory computer-readable storage medium, selecting the desired integration time, according to the third aspect itself or any of the foregoing implementations of the third aspect, includes selecting the longer of the first integration time and the second integration time.

[0195] In a fourth implementation of the non-transitory computer-readable storage medium, according to the third aspect itself or any of the foregoing implementations of the third aspect, the instructions further cause the processor to set a flag to indicate whether the first integration time or the second integration time is selected as the desired integration time; and to limit the desired integration time between a minimum and a maximum integration time.

[0196] In a fifth implementation of the non-transitory computer-readable storage medium, according to the third aspect itself or any of the foregoing implementations of the third aspect, the calibration data includes a calibration distance, the signal strength at the calibration distance, and the reflectivity at the calibration distance, and wherein the user input includes a minimum reflectivity, a maximum sigma, and a minimum of the maximum ranging distance.

[0197] Although this specification has been described in detail, it should be understood that various changes, substitutions, and alterations can be made without departing from the spirit and scope of this disclosure as defined by the appended claims. In the various drawings, the same elements are designated by the same reference numerals. Furthermore, the scope of this disclosure is not intended to be limited to the specific embodiments described herein, as it will be readily understood from this disclosure by those skilled in the art that existing or future processes, machines, manufactures, material compositions, apparatuses, methods, or steps can perform substantially the same functions or achieve substantially the same results as the corresponding embodiments described herein. Therefore, the appended claims are intended to include such processes, machines, manufactures, material compositions, means, methods, or steps within their scope.

[0198] Therefore, the specification and drawings are to be considered merely as a description of this disclosure as defined by the appended claims, and are to be considered to cover any and all modifications, variations, combinations or equivalents falling within the scope of this disclosure.

Claims

1. A system for controlling the integration time in a Time-of-Flight (ToF) device, the system comprising: The signal amplifier circuit is configured as follows: Receive calibration data and user input, and Calculate the desired signal rate and ambient rate; The distance parameter calculator circuit is configured to calculate the first integration time based on the desired signal rate and the ambient rate; A sigma parameter calculator circuit is configured to calculate the second integration time based on the desired signal rate, ambient rate, and maximum sigma. as well as An integration time controller is configured to select a desired integration time based on a first integration time and a second integration time, wherein the ToF device is configured to operate at the desired integration time.

2. The system according to claim 1, wherein the calibration data includes a calibration distance, the signal strength at the calibration distance, and the reflectivity at the calibration location.

3. The system of claim 1, wherein the user input includes the minimum values ​​of minimum reflectivity, maximum sigma, and maximum ranging distance.

4. The system of claim 1, wherein the signal scaler circuit is further configured to adjust the desired signal rate based on the inverse square law of distance.

5. The system of claim 1, wherein the distance parameter calculator circuit is configured to calculate the first integration time based on the signal confidence value and the ambient noise floor.

6. The system of claim 1, wherein the sigma parameter calculator circuit is configured to calculate the second integration time based on the pulse width and bin width of the ToF device.

7. The system according to claim 1, wherein the integral time controller is further configured to: The setting indicates whether to select the first integration time or the second integration time; and The desired integration time is limited to between the minimum integration time and the maximum integration time.

8. A method for controlling the integration time in a Time-of-Flight (ToF) device, the method comprising: Receive calibration data and user input; Calculate the desired signal rate and ambient rate; The first integration time is calculated based on the distance parameter using the desired signal rate and the ambient rate; The second integration time is calculated based on the desired signal rate, ambient rate, and sigma parameter of maximum sigma. Select the desired integration time based on the first integration time and the second integration time; as well as The ToF device is configured to operate at the desired integration time.

9. The method of claim 8, further comprising updating the desired signal rate and the ambient rate for each measurement frame of the ToF device.

10. The method of claim 8, wherein calculating the desired signal rate comprises scaling the calibrated signal strength based on the ratio between the desired minimum reflectivity and the calibrated reflectivity.

11. The method of claim 8, wherein selecting the desired integration time includes selecting the longer of the first integration time and the second integration time.

12. The method of claim 8, further comprising: A flag is set to indicate whether the first integration time or the second integration time is selected as the desired integration time; as well as The desired integration time is limited to between the minimum integration time and the maximum integration time.

13. The method of claim 8, wherein the calibration data includes a calibration distance, the signal strength at the calibration distance, and the reflectivity at the calibration location.

14. The method of claim 8, wherein the user input includes the minimum values ​​of minimum reflectivity, maximum sigma, and maximum ranging distance.

15. A non-transitory computer-readable storage medium storing computer instructions for determining integration time in a Time-of-Flight (ToF) device, the instructions causing the processor, when executed by a processor, to: Receive calibration data and user input; Calculate the desired signal rate and ambient rate; The first integration time is calculated based on the distance parameter using the desired signal rate and the ambient rate; The second integral time is calculated based on the sigma parameter using the desired signal rate, ambient rate, and maximum sigma. Select the desired integration time based on the first integration time and the second integration time; as well as Output the desired integration time used to configure the ToF device.

16. The non-transitory computer-readable storage medium of claim 15, wherein the instructions further cause the processor to update the desired signal rate and the ambient rate for each measurement frame of the ToF device.

17. The non-transitory computer-readable storage medium of claim 15, wherein calculating the desired signal rate includes scaling the calibrated signal strength based on the ratio between the desired minimum reflectivity and the calibrated reflectivity.

18. The non-transitory computer-readable storage medium according to claim 15, wherein, Selecting the desired integration time includes selecting the longer of the first integration time and the second integration time.

19. The non-transitory computer-readable storage medium of claim 15, wherein the instructions further cause the processor to: A flag is set to indicate whether the first integration time is selected as the desired integration time or the second integration time is selected as the desired integration time; and The desired integration time is limited to between the minimum integration time and the maximum integration time.

20. The non-transitory computer-readable storage medium of claim 15, wherein the calibration data includes a calibration distance, a signal strength at the calibration distance, and a reflectivity at the calibration location, and wherein the user input includes a minimum reflectivity, a maximum sigma, and a minimum of the maximum ranging distance.

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