CALIBRATION OF FIELD TRIANGULATION SENSORS IN THE PIXEL DOMAIN

Abstract

An apparatus and associated methods relate to a field-adjustable distance sensor configured to translate a sensor transfer function by a substantially constant value in a position domain by calibration at one or more known distances. In an illustrative example, the transfer function may correlate multiple distances with corresponding position vectors that describe the position of a light signal at a receiver. The receiver may generate, for example, a detection signal that corresponds to the position at the receiver of a light signal reflected by a target. A control circuit may generate, for example, a position vector in response to the detection signal. A calibration constant (C) may be generated, for example, as a function of a known distance from the target and the position vector. C may be applied, for example, to translate the transfer function in the position domain.Several methods can profitably reduce a nonlinear error in a distance sensor.

Description

CALIBRATION OF FIELD TRIANGULATION SENSORS IN THE PIXEL DOMAIN CROSS REFERENCE TO RELATED APPLICATIONS This application is a continuation of U.S. application serial number 17 / 303,061, entitled Pixel Domain Field Calibration of Triangulation Sensors, filed by Wade Oberpriller, et al., on May 19, 2021, and claims the benefit of that application. This application and U.S. application serial number 17 / 303,061 both claim the benefit of U.S. provisional application serial number 63 / 158,697, entitled NonContact Motion Detection Sensor Utilizing Distance and Intensity Statistics, filed by Wade Oberpriller, et al., on March 9, 2021. This application incorporates the entire content of the application(s) mentioned above by reference. The subject matter of this application may have common inventive authorship and / or may be related to the subject matter of the following applications: • U.S. application serial number 17 / 072,028, entitled Image-Based Jam Detection, filed by Wade Oberpriller, et al., on October 15, 2020; • U.S. application serial number 62 / 916,087, entitled Imaging System Using Triangulation, filed by Wade Oberpriller, et al., on October 16, 2019; and, • U.S. application serial number 62 / 924,020, entitled Imaging System Using Triangulation, filed by Wade Oberpriller, et al., on October 21, 2019. This application incorporates the entire content of the application(s) mentioned above herein by reference. TECHNICAL FIELD Several modalities refer in general terms to the field calibration of distance sensors. BACKGROUND OF THE INVENTION Distance sensors can be used in various industrial, commercial, and / or residential environments. By way of example, and without limitation, distance sensors can be used to monitor operator presence, movement, jamming, quality control, or any combination thereof. Distance sensors can be configured, for example, to detect the presence of an object within a detection window, at any point in front of the sensor, or any combination thereof. Distance sensors can be configured, for example, to determine distance based on the spatial position of an electromagnetic signal reflected by one or more sensing elements. Spatial position-based distance sensors can include, but are not limited to, infrared sensors, laser sensors (triangulation), or some combination thereof. A sensor might include, for example, at least one emitter configured to emit an electromagnetic signal, at least one sensing element configured to receive a reflection of the electromagnetic signal, and a control circuit configured to determine a distance based on the position of the electromagnetic signal reflected by the at least one sensing element. BRIEF DESCRIPTION OF THE INVENTION An apparatus and associated methods relate to a field-adjustable distance sensor configured to translate a sensor transfer function by a substantially constant value in a position domain by calibration at one or more known distances. In an illustrative example, the transfer function may correlate multiple distances with corresponding position vectors that describe the position of a light signal at a receiver. The receiver may, for example, generate a detection signal that corresponds to the receiver's position of a light signal reflected from a target. A control circuit may, for example, generate a position vector in response to the detection signal. A calibration constant (C) may be generated, for example, as a function of a known target distance and position vector. C may be applied, for example, to translate the transfer function in the position domain.Several methods can profitably reduce a nonlinear error in a distance sensor. Several modes can achieve one or more advantages. For example, some modes can effectively recalibrate a sensor to reduce an error introduced by a shift in a position transfer function (e.g., pixel position) versus sensor distance. In several modes, a calibration constant can be effectively generated based on a single measurement and calibration. Several modes can effectively reduce a random measurement error at a specific distance and / or sampling cycle by using multiple calibration cycles and / or distances. Several modes can effectively calibrate and / or maintain calibration according to a (predetermined) calibration threshold (e.g., measurement cycles, time). In several modes, a (calibrated) distance can be effectively determined from the position of a signal reflected at a receiver. zncn Ln / eznz / B / YiAi Several modes that provide a calibrated lookup table (LUT) (e.g., distance:position, distance correction, position vector correction) can advantageously reduce or eliminate the error between a measured distance and an actual distance while reducing and / or eliminating runtime performance costs. In several modes, a distance can, for example, be advantageously calibrated by applying a calibrated sensor characteristic profile. In several modes, a distance can, for example, be advantageously calibrated by retrieving a distance correction generated based on a calibrated sensor characteristic profile. Several modalities can advantageously improve the accuracy of a zero / space teaching method by exploiting a nonlinear relationship in the distance domain between the distance to a target and the position of a light beam reflected from the target at a receiver. Several modalities can also advantageously provide a more accurate and / or simpler (field) calibration method (e.g., by using one or more calibration points). In several methods, displacement calibration in the position domain of a sensor's transfer function can effectively reduce error within a predetermined accuracy threshold. For example, several methods can provide rapid field calibration to improve and / or restore accuracy by presenting one or more targets at one or more known distances. In several methods, the function can be effectively calibrated to the magnitude of each sensor accuracy error at one or more taught distances. Details of various embodiments are presented in the accompanying figures and in the description below. Other features and advantages will become apparent from the description and figures, and from the claims. BRIEF DESCRIPTION OF THE FIGURES Figure 1 illustrates an example field calibratable distance sensor (FCDS) in an example use case scenario. Figure 2 illustrates an example FCDS operating method. Figure 3 illustrates an example block diagram of an FCDS configured to generate a sensor position vector calibration constant. Figure 4 illustrates an example FCDS calibration method from Figure 3. Figure 5 illustrates an example FCDS operating method from Figure 3 to determine distance by applying a sensor position vector calibration constant. Figure 6 illustrates an example block diagram of an FCDS configured to generate a lookup table of calibrated distances from a sensor position vector calibration constant zncn Ln / eznz / e / YiAi. Figure 7 illustrates an example calibration method of the FCDS from Figure 6. Figure 8 illustrates an example operating method of the FCDS from Figure 6 to determine distance by retrieving a calibrated distance from the calibrated distance lookup table. Figure 9 illustrates an example block diagram of an FCDS configured to generate a distance sensor characteristic curve fitting calibration constant. Figure 9 illustrates an example calibration method of the FCDS. Figure 9 illustrates an example operating method of the FCDS for determining distance by determining a distance correction by applying the curve-fit calibration constant. Figure 2 illustrates an example block diagram of an FCDS configured to generate a lookup table of distance corrections. Figure 13 illustrates an example method for calibrating the FCDS from Figure 12. Figure 14 illustrates an example method of operating the FCDS of Figure 12 to determine distance by applying a distance correction retrieved from the distance correction lookup table. Figure 15 illustrates an example triangulation sensor geometry. Figure 16 illustrates accuracy errors in example distance sensors after an aging process. Figure 17A illustrates example calibration results using a generated zero / space teaching method. Figure 17B illustrates example results of calibrating the same sensor shown in Figure 17A with a constant displacement in the position domain. Figure 18 illustrates example pixel-domain displacements of a pixel:distance transfer function for a distance sensor. Figure 19 illustrates example normalized displacement results from a displacement field calibration in the single-point pixel domain. Figure 20 illustrates the example residual accuracy results of the displacement field calibration in the single-point pixel domain illustrated in Figure 19. Figure 21 illustrates a curve fit to an example normalized accuracy error profile for distance sensors after an aging process. Figure 22 illustrates example residual accuracy results from a field calibration in the single-point distance domain using the curve fitting illustrated in Figure 21. zncn Ln / eznz / e / YiAi Similar reference symbols in the various figures indicate similar elements. DETAILED DESCRIPTION OF THE INVENTION To facilitate understanding, this document is organized as follows. First, to help introduce the discussion of various modalities, a field-calibratable distance sensor (FCDS) system is introduced with reference to Figures 1-2. Second, this introduction leads to a description, with reference to Figures 2-14, of some example FCDS modalities. Third, with reference to Figures 15-21, the FCDS devices and methods disclosed herein are described as applied to example use cases. Finally, the document discusses additional modalities, example applications, and related aspects of FCDS. Figure 1 illustrates an example field-calibratable distance sensor (FCDS) in an example use case scenario. In the illustrated system 100, an FCDS 105 is equipped with an emitter 110 (e.g., one or more emitter circuits) and an emitting lens in a first configuration 115A (e.g., a factory configuration). The emitter 110 projects an electromagnetic signal (EMS) 120A (e.g., an optical beam) through the emitting lens in configuration 115A. The EMS 120A is reflected from a target 125 at a distance DT from the FCDS 105. At least a portion of the EMS 120 is reflected from the target, generating a reflected EMS (REMS) 130A. The REMS 130A passes through a receiving lens in a first configuration 135A (e.g., factory configuration) and impacts the receiver 140. As illustrated, the 140 receiver includes multiple spatially distributed sensing elements. For example, the 140 receiver can be configured as a multipixel array (e.g., ID, 2D, 3D) of pixels. Each pixel can, for example, include an individual sensing element. Each element can, for example, be a photosensitive element. A photosensitive element can, by way of example and not limitation, be a photodiode and / or another photoelectric element. A controller 150 (e.g., a control circuit, processor, ASIC, FPGA) can determine a measured distance based on the incidence position of the REMS 130A on the receiver 140. In the illustrated example, the REMS 130A passes through the lens in the first configuration 135A to strike a first pixel 145A of the receiver 140. The controller 150 can, for example, determine a first measured distance (DM1) based on the position of the first pixel 145A on the receiver 140. The receiver 140 can, for example, generate a signal corresponding to the activation of pixel 145A. The controller 150 can, by way of example and not as a limitation, determine a first position vector from the signal. The controller 150 can retrieve (e.g., from a lookup table) a distance corresponding to the first position vector. The first configuration 115A of the transmitting lens, EMS 120A, REMS 130A, and the first configuration 135A of the receiving lens can, by way of example and not limitation, correspond to a factory configuration of the FCDS 105 (e.g., a new configuration). In the illustrated example, the transmitting lens has been shifted from the first configuration 115A to a second configuration 115B. Similarly, the receiving lens has been shifted from the first configuration 135A to a second configuration 135B. The change in configuration may, for example, correspond to component aging, stress, impact, vibration, other (mechanical) inputs, or some combination thereof. In several modalities, a housing, lens(es), emitter, receiver, other components in the optical path of an emitted and / or reflected EMS, or some combination of the above, may change in relation to each other. As illustrated, the change in lens configuration, relative to the FCDS 105 housing, emitter 110, and receiver 140, causes a corresponding change in the optical path. Emitter 110 launches an EMS 120B, which is displaced downwards compared to its previous (i.e., original) path. EMS 120B strikes target 125, and at least a portion of EMS 120B is reflected as REMS 130B. REMS 130B travels along a different path than REMS 130A, at least due to the change in the emitting lens configuration. Furthermore, as REMS 130B passes through the receiving lens in the second configuration 135B, the altered configurations cause an additional change relative to the original path relative to the receiver 140. Therefore, REMS 130B impacts the receiver 140 at a second pixel 145B. FCDS 105 can, for example, thus determine a different (e.g., inaccurate) measured distance (DM2) even though the target distance DT 125 relative to FCDS 105 has not changed. In the illustrated example, a user 155 operates an input element 160. The input element 160 is operatively coupled to the controller. The input element 160 can be configured to generate a calibration signal. The controller 150 can respond to the calibration signal by entering a teach mode. In teach mode, the controller 150 can compare at least one position vector generated by the second REMS 130B with at least one expected position vector and / or distance corresponding to the target(s) 125 used for calibration. In various modes, the comparison can be performed, by way of example but not limitation, directly (e.g., by directly comparing position vectors), indirectly (e.g., by applying a function after looking up a corresponding value), or some combination thereof. In the illustrated example, a graph 165 illustrates a spatial domain (e.g., pixel) transfer function that defines a correlation between (1) a (physical) distance to a target on the horizontal axis and (2) a position (e.g., as defined by a position vector) of a REMS (e.g., 130A, 130B) in the receiver 140 on the vertical axis. A first transfer function 170 may, for example, correspond to an original calibration of the FCDS 105 (e.g., according to zncn Ln / eznz / B / YiAi, a factory calibration). A second transfer function 175 may, for example, correspond to an actual transfer function of the FCDS 105 after aging and / or stress. For example, the second transfer function 175 can define a relationship between a position of a REMS on the sensor (for example, the receiver 140) and a corresponding measured distance to a target when the lenses are in configuration 115B and 135B.As illustrated, in the spatial domain, the shift of the transfer function is substantially constant. In the illustrated example, a transfer function 170 (original) has been shifted upward in the position domain (e.g., pixel) by a constant shift in position (e.g., pixel position) as illustrated by the second transfer function 175. During calibration operations (e.g., in teach mode), the controller 150 can generate at least one correction constant C based on the true distance (DT) from the calibration target 125 and an actual (measured) position vector VM generated as a result of the activation of pixel 145B by the REMS 130B. As illustrated, the correction constant C can be set to shift a current transfer function 175 in the position domain (e.g., pixel) back toward a desired (e.g., original, exact) transfer function 170. Therefore, the controller 150 can profitably recalibrate the FCDS 105 to reduce the error introduced by a shift in the transfer function. In several modes, calibration can be performed in the field, as illustrated. In several modes, calibration can, by way of example but not limitation, be performed as a single-point calibration. For example, a target can be presented at a known distance (e.g., DT), and the FCDS 105 can be operated to enter a teaching mode. The sensor can then be recalibrated based on a comparison between the known distance and a measured position vector (e.g., generated from pixel 145B, which is incident on the REMS 130B). A calibration constant can be usefully generated based on this simple measurement and calibration. In various configurations, one or more targets can be presented at one or more distances. For example, one, two, three, or more targets can be presented at one or more known distances. Each target can, for example, be presented at one, two, three, or more known distances. The resulting position vector(s) and / or corresponding measured (uncalibrated) distances can, by way of example but not limitation, be averaged and / or otherwise used to generate a calibration constant C. Thus, a random measurement error at a specific distance or in a specific sampling cycle can be advantageously reduced and / or eliminated. Figure 2 illustrates an example method of operating an FCDS. In the illustrated method 200, a sensor (e.g., 105 / / ) receives a start signal 205.The start signal may, by way of example but not limitation, be an automatically generated signal, a program-generated signal, a manually generated signal, or a combination thereof. The start signal may, by way of example but not limitation, correspond to power-up, the start of predetermined operations (e.g., activation of a conveyor belt, activation of machine protection), another appropriate trigger, or some combination thereof. If the sensor has been calibrated 210, then the method proceeds to measure the distance in a step 230. If the sensor has not been calibrated 210, then the method proceeds to determine whether the sensor can be self-calibrated 215. If the sensor cannot be self-calibrated 215, then the process waits for the receipt of a calibration signal (for example, programmatically, through manual input from a user) 220. The insert can be self-calibrated 215, or a calibration signal has been received 220, then calibration is performed 225. In various modes, by way of example but not limitation, calibration can be carried out in accordance with the description at least with reference to Figures 4, 7, 10 and 13. Once the sensor has been calibrated 225, or if the sensor is already calibrated 210, then the method proceeds to measure the distance in a step 230. In various modes, the distance can be measured once, periodically, repeatedly, continuously, or some combination thereof. In various modes, the distance can, for example, be measured in accordance with the description at least with reference to Figures 5, 8, 11, and 14. After the sensor measures the distance (230), if further processing (235) is not planned (for example, the distance measurement has been completed), then the method terminates. If further processing (235) is required, then it is determined whether a calibration threshold (240) has been reached. In various modes, a calibration threshold may, by way of example but not limitation, be a cycle count (for example, recalibrate after X cycles), a timer (for example, recalibrate after Y time units), or some combination thereof. If the calibration threshold (240) has not been reached, then the method returns to step (230) to measure the distance. If the calibration threshold (240) has been reached, then the method returns to step (215) to recalibrate and continue the measurement. Thus, various modes can advantageously calibrate and / or maintain calibration according to a (predetermined) calibration threshold. Figure 3 illustrates an example block diagram of an FCDS configured to generate a sensor position vector calibration constant. The illustrated FCDS 300 includes a processor 305. The processor 305 is operationally coupled (e.g., electrically) to the transmitter 110 and the receiver (e.g., a set of spatially distributed receivers) 140. The processor 305 is operationally coupled (e.g., electrically) to at least non-volatile memory (NVM) modules 310, 315, 320, and 325. In various configurations, the NVM modules can be combined and / or additional NVM modules can be provided. zncn Ln / eznz / e / YiAi In the illustrated example, the NVM 310 module is a position-distance lookup table (LUT). The lookup table can, for example, map each of multiple position vectors that identify a REMS location on receiver 140 to a corresponding measured distance value. The NVM 315 module includes a program of operations configured to be executed as runtime instructions on processor 305. The runtime instructions can, for example, be configured to cause processor 305 to perform runtime operations described at least with reference to Figure 5. The NVM 320 module includes a program of operations configured to be executed as calibration instructions (for example, teach mode) on processor 305.The calibration instructions can, for example, be configured to cause the 305 processor to perform calibration operations described at least with reference to Figure 4. The NVM 325 module includes a calibration constant (for example, C), which can be determined during calibration operations. In the illustrated example, the 305 processor is operationally coupled with a 330 random access memory (RAM) module. In various configurations, RAM modules can be combined and / or additional RAM modules can be provided. As illustrated, the 330 RAM module includes the calibration constant at least some of the time, such as when it is generated during calibration operations and / or during runtime operations that apply the calibration constant. Figure 4 illustrates an example FCDS calibration method from Figure 3. In the illustrated method, a signal 405 is received to cause the FCDS 300 to enter a calibration mode. The processor 305 can, for example, execute operations stored in NVM 320. The calibration mode can, for example, include a teach mode configured to allow a user to teach one or more correct distances to the sensor. A calibration signal 410 is received, corresponding to a true distance (DT) from a calibration target from the FCDS 300. The calibration signal can, for example, correspond to a manual input for calibration, program calibration command(s) (e.g., at startup, periodically, per measurement cycle), or some combination thereof. An expected position vector (VT) corresponding to DT is determined 415. VT can, for example, be determined by retrieving a position vector from the LUT's NVM 310 that corresponds to the distance DT. The emitter 110 generates (for example, as operated by the processor 305) 420 a light signal at the calibration target. A detection signal 425 is received from the receiver 140 that corresponds to a position of a reflection of the light signal from the target that strikes the receiver 140. A detected position vector (VM) is generated 430 from the detection signal and corresponds to a position of the light signal reflected at the receiver 140. VM is compared to VT. If the difference between VT and VM is less than a calibration threshold (TH) of 435 (default), then no calibration is needed, and the process ends. If the difference is not less than TH 435, then a calibration constant (C) is generated. In the illustrated example, C is a position vector (e.g., pixel) offset (substantially) equal to the difference between VT and VM. C is then stored (in the NVM module 325), and the calibration process ends. Therefore, C can be accessed and applied (e.g., addition, subtraction) to a measured position vector (e.g., VM) to generate a calibrated position vector such that a given distance is calibrated to reduce or eliminate an error between the measured distance and the actual distance. Figure 5 illustrates an example FCDS operating method from Figure 3 for determining distance by applying the sensor position vector calibration constant. In the illustrated method 500, an emitted light signal is generated 505 by the emitter 110. The processor 305 can, for example, execute operations stored in NVM 315 to operate the emitter 110 and / or perform other runtime operations. If a reflected light signal is not detected 510 at the receiver 140, then the method returns to step 505. If a reflected light signal is detected 510, then a detection signal is received 515 from the receiver 140, which corresponds to a position of the reflected light signal relative to a measurement target at the receiver 140. A measured position vector VM is determined 520 from the detection signal.If a calibration constant C is set to 525 (e.g., generated by method 400, stored in NVM module 325, and / or loaded into RAM module 330), then a corrected position vector VC is generated by applying C to VM. For example, as illustrated, VC = VM + C. Once the corrected position vector is generated, a distance signal (DC) is generated from the corrected position vector VC. If C is not set to 525 (e.g., no calibration has been performed, no calibration is required), then DC is generated from the measured position vector VM. For example, DC can be generated by retrieving a distance corresponding to the position vector from the LUT's NVM 310. Therefore, a (calibrated) distance can be usefully determined from the position of a signal reflected at receiver 140.The distance can, for example, be usefully calibrated by applying a calibration constant. Figure 6 illustrates an example block diagram of an FCDS configured to generate a lookup table of calibrated distances from a sensor position vector calibration constant. The illustrated FCDS 600 includes a processor 605. The processor 605 is operationally coupled (e.g., electrically) to the transmitter 110 and the receiver (e.g., a set of spatially distributed receivers) 140. The processor 605 is operationally coupled (e.g., electrically) to at least non-volatile memory (NVM) modules 610, 615, and 620. In various configurations, NVM modules can be combined and / or additional NVM modules can be provided. In the illustrated example, an NVM 610 module is a position-distance lookup table (LUT). The lookup table can, for example, map each of multiple position vectors that identify a REMS location on receiver 140 to a corresponding measured distance value. The NVM 615 module includes a program of operations configured to be executed as runtime instructions on processor 605. The runtime instructions can, for example, be configured to have processor 605 perform runtime operations described at least with reference to Figure 8. The NVM 620 module includes a program of operations configured to be executed as calibration instructions (e.g., teach mode) on processor 605.The calibration instructions can, for example, be configured to make the 605 processor perform the calibration operations described at least with reference to Figure 7. In the illustrated example, the 305 processor is operationally coupled with a 630 random access memory (RAM) module. In various configurations, RAM modules can be combined and / or additional RAM modules can be provided. As illustrated, the 630 RAM module includes the calibration constant at least some of the time, for example, when it is generated during calibration operations. Figure 7 illustrates an example calibration method for the FCDS of Figure 6. In the illustrated method, a signal is received to cause the FCDS to enter a calibration mode. The processor can, for example, execute operations stored in NVM. The calibration mode can, for example, include a teach mode configured to allow a user to teach one or more correct distances to the sensor. A calibration signal is received, which corresponds to a true distance (DT) from a calibration target taken from the FCDS. The calibration signal can, for example, correspond to a manual input for calibration, program calibration command(s) (e.g., at startup, periodically, per measurement cycle), or some combination thereof. An expected position vector (VT) corresponding to DT is determined 715. VT can, for example, be determined by retrieving a position vector from the LUT's NVM 610 corresponding to the distance DT. The emitter 110 generates (for example, as operated by the processor 605) 720 a light signal at the calibration target. A detection signal is received 725 from the receiver 140 corresponding to a position of a reflection of the light signal from the target that strikes the receiver 140. A detected position vector (VM) is generated 730 from the detection signal and corresponds to a position of the light signal reflected at the receiver 140. VM is compared to VT. If the difference between VT and VM is less than a calibration threshold (TH) 735 (default), then no calibration is needed, and the process ends. If the difference is not less than TH 735, then a calibration constant (C) is generated 740. In the illustrated example, C is a position vector (e.g., pixel) offset (substantially) equal to the difference between VT and VM. C is then applied to the LUT stored in NVM 610 to generate a calibrated LUT in a step 745 by offsetting each position value in the LUT by C. The calibrated LUT can, by way of example but not limitation, overwrite the LUT previously stored in NVM 610 and / or can be stored in a memory module. Therefore, a calibrated LUT can be accessed to determine a calibrated distance based on a measured position vector.A calibrated LUT can advantageously reduce or eliminate an error between the measured distance and an actual distance while minimizing and / or eliminating runtime realization costs. Figure 8 illustrates an example method of operating the FCDS of Figure 6 to determine distance by retrieving a calibrated distance from the calibrated distance lookup table. In the illustrated method, an emitted light signal is generated by an emitter. The processor can, for example, execute operations stored in NVM to operate the emitter and / or perform other runtime operations. If a reflected light signal is not detected at the receiver, the method returns to step 805. If a reflected light signal is detected, a detection signal is received from the receiver, corresponding to the position of the reflected light signal relative to a measurement target at the receiver. A measured position vector is determined from the detection signal. A distance signal (DC) is generated 825 from the measured position vector VM. For example, DC can be generated by retrieving a distance corresponding to a position vector from the calibrated LUT generated in accordance with the disclosures, at least with reference to Figure 7 (e.g., retrieved from NVM 610). Consequently, a (calibrated) distance can be usefully determined from the position of a signal reflected at the receiver 140. The distance can, for example, be usefully calibrated with minimal or no impact on runtime performance by using a calibrated lookup table. Figure 9 illustrates an example block diagram of an FCDS configured to generate a calibration constant for fitting a distance sensor characteristic curve. The illustrated FCDS 900 includes a processor 905. The processor 905 is operationally coupled (e.g., electrically) to the transmitter 110 and the receiver (e.g., an array of spatially distributed receivers) 140. The processor 905 is operationally coupled (e.g., electrically) to non-volatile memory (NVM) modules 910, 915, 920, 925, and 930. In various configurations, NVM modules can be combined and / or additional NVM modules can be provided. In the illustrated example, NVM module 910 is a position-distance lookup table (LUT). The lookup table can, for example, map each of multiple position vectors that identify a REMS location on receiver 140 to a corresponding measured distance value. NVM module 915 includes a program of operations configured to be executed as runtime instructions on processor 905. The runtime instructions can, for example, be configured to cause processor 905 to perform runtime operations described at least with reference to Figure 11. NVM module 920 includes a program of operations configured to be executed as calibration instructions (e.g., teach mode) on processor 905.The calibration instructions may, for example, be set to have the 905 processor perform calibration operations described at least with reference to Figure 10. In the illustrated example, the NVM 925 module includes a default curve fitting relationship. The curve fitting relationship can, by way of example and not limitation, include a default relationship between error and distance, error and position (e.g., pixel), another appropriate relationship, or some combination thereof. In various modes, the curve fitting relationship can, by way of example and not limitation, include linear, polynomial, exponential, logarithmic, or other appropriate function components, or some combination thereof. The NVM 930 module includes a calibration constant (e.g., C), which can be determined during calibration operations. In various modes, the default curve fitting can be updated (e.g., during calibration operations) based on the calibration constant and the result stored in a simple memory module.In the illustrated example, the 905 processor is operationally coupled to a 935 random access memory (RAM) module. In various configurations, RAM modules can be combined and / or additional RAM modules can be provided. As illustrated, the 935 RAM module includes the calibration curve fitting ratio at least some of the time, such as when it is generated during calibration operations and / or during runtime operations that apply the calibration constant. For example, the calibration curve fitting ratio might be a function of the default curve fitting stored in the 925 NVM module and the calibration constant stored in the 930 NVM module. Figure 10 illustrates an example calibration method for the FCDS in Figure 9. In the illustrated method, a signal is received to cause the FCDS to enter a calibration mode. The processor can, for example, execute operations stored in NVM. The calibration mode can include a teach mode configured to allow a user to teach one or more correct distances to the sensor. A calibration signal is received, which corresponds to a true distance (DT) from a calibration target taken from the FCDS. The calibration signal can be a manual input for calibration, program calibration command(s) (e.g., at startup, periodically, per measurement cycle), or some combination thereof. The emitter 110 generates (for example, as operated by processor 905) 1015 a light signal on the calibration target. A detection signal is received 1020 from receiver 140, corresponding to the position of a reflection of the light signal from the target that strikes receiver 140. A detected position vector (VM) is generated 1025 from the detection signal, corresponding to the position of the reflected light signal at receiver 140. A measured distance signal (DM) is generated 1030 from VM. For example, DM can be generated by retrieving a distance value from the LUT in NVM module 910 as a function of VM. DM is compared to DT. If the difference between DM and DT is less than a calibration threshold (TH) (default) of 1035, then no calibration is required, and the process ends. If the difference is not less than TH 1035, then a calibration constant (C) is generated. In the illustrated example, C is generated according to a correction distance (CD) substantially equal to the difference between DT and DM. For example, C could be a scalability factor of a polynomial (second-order) curve-fitting equation (e.g., stored in NVM module 925) that defines a default characteristic profile of the sensor. C is then stored (in NVM module 930), and the calibration process ends. Therefore, C can be accessed for application (e.g., scalability) with a characteristic profile (e.g., a curve-fitting equation stored in the NVM 925 module) at a measured distance to generate a calibrated distance.Therefore, calibrated distance measurement can reduce or eliminate an error between the measured distance and an actual distance. Figure 11 illustrates an example method of operating the FCDS of Figure 9 to determine distance by determining a distance correction through the application of the curve-fit calibration constant. In the illustrated method, a light signal is generated by emitter 110. Processor 905 can, for example, execute operations stored in NVM 915 to operate emitter 110 and / or to perform other runtime operations. If a reflected light signal is not detected 1110 at receiver 140, then the method returns to step 1105. If a reflected light signal is detected 1110, then a detection signal is received 1115 from receiver 140 that corresponds to a position of a reflected light signal zncn Ln / eznz / B / YiAi from a measurement target at receiver 140. A measured position vector VM is determined 1120 from the detection signal.A measured distance (DM) signal is generated 1125 from VM and the LUT stored in the NVM module 910. For example, the processor 905 can retrieve DM from the LUT based on VM. If a calibration constant C is set 1130 (e.g., generated by method 1000, stored in NVM module 925, and / or loaded into RAM module 930), then a correction distance (DS) is generated 1135 by applying the calibrated characteristic profile (e.g., by C) (e.g., curve-fit ratio) to DM. For example, DS can be an output of a characteristic profile ratio depending on DM and C inputs. Once the corrected distance is generated 1135, a calibrated distance (DC) signal is then generated 1140 from DM and DS, and DC can be produced as the final measured distance. If C is not set 1130 (e.g., no calibration has been performed, no calibration is required), then no correction is applied, and DM can be produced as the final measured distance.Therefore, a (calibrated) distance can be usefully determined from the position of a signal reflected at receiver 140. The distance can, for example, be usefully calibrated by applying a characteristic profile of a calibrated sensor. Figure 12 illustrates an example block diagram of an FCDS configured to generate a distance correction lookup table. The illustrated FCDS 1200 includes a processor 1205. The processor 1205 is operationally coupled (e.g., electrically) to the transmitter 110 and the receiver (e.g., a spatially distributed set of receivers) 140. The processor 1205 is operationally coupled at least (e.g., electrically) to non-volatile memory (NVM) modules 1210, 1215, 1220, 1225, and 1230. In various configurations, NVM modules can be combined and / or additional NVM modules can be provided. In the illustrated example, an NVM module 1210 is a position-distance lookup table (LUT). The lookup table can, for example, map each of multiple position vectors that identify a REMS location on receiver 140 to a corresponding measured distance value. The NVM module 1215 includes a program of operations configured to be executed as runtime instructions on processor 1205. The runtime instructions can, for example, be configured to cause processor 1205 to perform runtime operations described at least with reference to Figure 14. The NVM module 1220 includes a program of operations configured to be executed as calibration instructions (for example, teach mode) on processor 1205.The calibration instructions can, for example, be configured to cause the 1205 processor to perform calibration operations described at least with reference to Figure 13. In the illustrated example, the NVM 1225 module includes a default curve fitting ratio. zncn Ln / eznz / B / YiAi The curve fitting relationship may, by way of example and not limitation, include a predefined relationship between error and distance, error and position (e.g., pixel), another appropriate relationship, or some combination thereof. In several modes, the curve fitting relationship may, by way of example and not limitation, include linear, polynomial, exponential, logarithmic, other appropriate function components, or some combination thereof. The NVM 1230 module includes a calibration constant (e.g., C), which can be determined during calibration operations. In several modes, the default curve fitting can be updated (e.g., during calibration operations) based on the calibration constant, and the result can be stored in a single memory module. In the illustrated example, the 1205 processor is operatively coupled to a 1235 random access memory (RAM) module. In various modes, RAM modules can be combined and / or additional RAM modules can be provided. Figure 13 illustrates an example calibration method for the FCDS in Figure 12. In the illustrated method, a signal is received to cause the FCDS to enter a calibration mode. The processor can, for example, execute operations stored in NVM. The calibration mode can include a teach mode configured to allow a user to teach one or more correct distances to the sensor. A calibration signal is received, which corresponds to a true distance (DT) from a calibration target taken from the FCDS. The calibration signal can be a manual input for calibration, program calibration command(s) (e.g., at startup, periodically, per measurement cycle), or some combination thereof. The emitter 110 generates 1315 (for example, as operated by the processor 1205) a light signal on the calibration target. A detection signal is received 1320 from the receiver 140, corresponding to the position of a reflection of the light signal from the target that strikes the receiver 140. A detected position vector (VM) is generated 1325 from the detection signal, corresponding to the position of the reflected light signal at the receiver 140. A measured distance signal (DM) is generated 1330 from VM. For example, DM can be generated by retrieving a distance value from the LUT in the NVM module 1210 based on VM. DM is compared to DT. If the difference between DM and DT is less than a calibration threshold (TH) (default) 1335, then no calibration is needed, and the process ends. If the difference is not less than TH 1335, then a calibration constant (C) 1340 is generated. In the illustrated example, C is generated according to a correction distance (CD) substantially equal to the difference between DT and DM. For example, C could be a zncn Ln / eznz / B / YiAi (scalability) factor from a polynomial (second-order) curve-fitting equation (e.g., stored in NVM module 1225) that defines a default characteristic profile of the sensor. A correction LUT is then generated 1345 (e.g., stored in NVM module 1230), and the calibration process ends.The correction LUT can, for example, be generated by applying a calibrated characteristic profile (e.g., a curve-fitting equation stored in NVM module 1225 as calibrated by C) to multiple measured distances (e.g., corresponding to distances in the position LUT and distance stored in NVM module 1210) to generate a corresponding correction distance. Each measured distance and correction distance pair can then be stored in the correction LUT (e.g., stored in NVM module 1230). Consequently, the correction LUT can be applied to a distance measurement to generate a calibrated distance measurement. Therefore, calibration can reduce or eliminate the error between a calibrated measured distance and an actual distance. In several scenarios, the correction LUT can be omitted. A calibrated position-distance LUT can, by way of example and not limitation, be generated by applying a correction (e.g., as discussed in the section on generating the correction LUT). For example, a calibrated position-distance LUT can be generated by applying C (e.g., as a characteristic profile coefficient) to each of the multiple distances in the LUT to generate a calibrated distance. Corresponding position vectors in the LUT are then usefully mapped to calibrated distance values. Such scenarios can, for example, advantageously reduce and / or eliminate the impact of calibration on runtime performance. Figure 14 illustrates an example method of operating the FCDS in Figure 12 to determine distance by applying a distance correction retrieved from the distance correction lookup table. In the illustrated method, a light signal is generated by emitter 110. The processor can, for example, execute operations stored in NVM to operate emitter 110 and / or perform other runtime operations. If a reflected light signal is not detected 1410 at the receiver 140, then the method returns to step 1405. If a reflected light signal is detected 1410, then a detection signal is received 1415 from the receiver 140 that corresponds to a position of the reflected light signal from a measurement target at the receiver 140. A measured position vector VM is determined 1420 from the detection signal.A measured distance (DM) signal is generated 1425 from VM and the position / distance LUT stored in the NVM module 1210. For example, the processor 1205 can retrieve DM from the LUT based on VM. In some (unillustrated) modes, the processor 1205 can retrieve DM from a calibrated LUT zncn Ln / eznz / B / YiAi and the process can terminate. If a calibration constant C is set (e.g., generated by method 1300, stored in the NVM module 1225, and / or loaded into the RAM module 1235), then a correction distance (DS) is generated by retrieving, from the correction distance lookup table (LUT) stored in the NVM module 1230, the correction distance (DS) corresponding to DM. Once the corrected distance is generated, a calibrated distance (DC) signal is generated from DM and DS, and DC can be produced as the final measured distance. If C is not set (e.g., no calibration has been performed, calibration is not required), then no correction is applied, and DM can be produced as the final measured distance. Therefore, a (calibrated) distance can be usefully determined from the position of a signal reflected at the receiver.The distance can, for example, be usefully calibrated by retrieving a distance correction generated based on a characteristic profile of a calibrated sensor. Figure 15 illustrates an example triangulation sensor geometry. In the illustrated optomechanical system 1500, an emitter 1505 (e.g., LED, laser diode, avalanche photodiode, infrared emitter) emits a light beam through a lens 1510. The light beam is reflected from a target 1515. The reflected beam passes through a lens 1520 (e.g., a collimating lens) into a receiver 1525. According to the illustration, as the target 1515 moves toward the sensor, the location of the centroid of the received light shifts along the receiver 1525 (e.g., a spatially distributed assembly) away from the emitter 1505. For conventional purposes, the far location of the receiver 1525 refers to the portion that is closest to the emitter 1505. As illustrated, equal incremental steps of the target 1515 toward the sensor result in progressively larger steps in the beam position. light reflected in the receiver 1525. Figure 16 illustrates example accuracy errors in distance sensors after an aging process. In the illustrated example, a set of sensors were manufactured and aged through natural aging and by subjecting them to thermal and mechanical stress. After this aging period, the error on the calibration map as a function of distance was observed and recorded. As can be seen in the illustrated scatter plot of accuracy (mm) versus distance (mm), the error increases non-linearly with distance. For example, in a near range (defined in the illustrated example as up to approximately 500 mm), the error is less than 20 mm. In a far range (defined in the illustrated example as beyond approximately 500 mm), the error increases non-linearly with distance. Figure 17A illustrates example calibration results using a zero / generated space teaching method. In the example accuracy (mm) relative to distance (mm) plot 1700, the accuracy of an aging, uncalibrated sensor is shown by the scatter plot 1705. A conventional zero / generated space teaching calibration is performed by teaching the sensor with a target at a known near distance (e.g., nearly 0 mm) and a known far distance (e.g., approximately 3000 mm). All error is assumed to be linear between the two teaching points. A new calibration (e.g., calibration map) is generated which correlates distance with position as adjusted by the linear calibration relationship defined by the near and far calibration points. The accuracy of the sensor after the zero / generated space calibration is shown by the scatter plot 1710.As can be seen, even though the maximum error is reduced (for example, from approximately 260 mm to 3000 mm to approximately -70 mm to approximately 1400 mm), a greater amount of error is now introduced in portions of the range. For example, in the illustrated example, the error at approximately 500 mm is increased from approximately 10 mm to approximately 30 mm. Since a linear assumption is made, and the relationship between the position of a reflected signal and the distance is not linear, the error is now maximized and / or introduced, for example, between the calibration (teaching) points. Figure 17B illustrates example calibration results for the same sensor as that illustrated in Figure 17A with a constant displacement in the position domain. The (uncalibrated) sensor was calibrated to introduce a substantially constant displacement in the position domain. In the illustrated example, the uncalibrated sensor was taught using a target at a unique, known distance, as disclosed at least with reference to Figure 4. The known distance was greater than or equal to 500 mm. An expected pixel position of the centroid of a corresponding reflected light beam from the target was determined based on the known distance to the target. The expected pixel position was compared with the actual pixel position of the centroid of the reflected light beam.A pixel position offset (e.g., as a calibration constant) was determined based on a comparison (e.g., the difference between an expected pixel position and the actual pixel position). The pixel position offset (calibration constant) was applied to all distances to uniformly shift the pixel position for each distance by the calibration constant. The resulting graph of accuracy versus actual distance is illustrated in a comparison graph 1701 by means of a scatter plot 1715. In the illustrated example, the error was substantially reduced to + / -20 mm. Furthermore, no substantial error was introduced in a central region of the distance range compared to the scatter plot 1710 illustrating the generated zero / space teaching method applied to the same sensor. Therefore, several modalities can profitably improve accuracy relative to a linearly generated zero / space teaching method by utilizing the nonlinear relationship in the distance domain (e.g., illustrated at least in Figure 15) between the distance to a target and the position of a light beam reflected from the target at a receiver.Therefore, several modalities can advantageously provide a more accurate and / or simpler (field) calibration method (e.g., by using one or more calibration points). Figure 18 illustrates example pixel-domain shifts of a pixel-distance transfer function for a distance sensor. The transfer functions illustrated in the example graph 1800 can, by way of example and not limitation, define a distance-location relationship of REMS in a receiver (e.g., 140, 1525), such as a set of spatially distributed photosensitive pixels. For example, the geometry disclosed with reference to Figures 1 and 15 can be defined, for example, by a nonlinear curve as shown by transfer function plot 1805. Transfer function plot 1805 can, for example, define a position-distance characteristic of a sensor when it is configured to measure distance within a predetermined accuracy threshold. For example, transfer plot 1805 can represent a new sensor condition. The sensor, for example, may not have been subjected to aging or exposed to stress conditions. Aging, stress conditions, or some combination thereof can, by way of example and not limitation, cause a shift in the transfer function. For example, various components (e.g., emitter, receiver, lens(es), housing) may have shifted relative to each other. In a first illustrated example, the transfer function is shifted upward, as illustrated by graph 1810, by a substantially constant value C+. Therefore, a given pixel location now corresponds to a shorter distance. For example, in the illustrated example, a pixel location 100,000 originally corresponded to approximately 500 mm, and now corresponds to approximately 400 mm. Therefore, if the sensor is still calibrated based on the transfer function graph 1805 that was applied before the transfer function shift, at 500 mm, the sensor would have an error of approximately 100 mm.Similarly, in a second illustrated example, the transfer function is shifted downward, as illustrated by graph 1815, by a substantially constant value C. Therefore, a given pixel function now corresponds to a farther distance. For example, in the illustrated example, the location of pixel 100,000 now corresponds to approximately 600 mm. Therefore, if the sensor continues to be calibrated based on the transfer function graph 1805 that was applied before the transfer function shift, at 500 mm, the sensor would now have an error of approximately 100 mm. As illustrated, the distance error varies nonlinearly with distance (as can be seen in Figure 16). However, the transfer function shifts substantially by a constant amount in the pixel domain. Several methods offer field calibration of a sensor by determining a calibration constant that results in a substantially constant shift in the position-distance transfer function. Therefore, several methods can advantageously provide accurate and / or efficient (e.g., single-point) calibration of one or more (triangulation) sensors. Figure 19 illustrates example normalized offset results from a single-point pixel domain offset field calibration. The sensors illustrated in the scatter plot 1600 of Figure 16 were calibrated by teaching at a single distance to generate and apply a pixel shift calibration constant to a lookup table (LUT) that correlates pixel position-distance (e.g., defined by a transfer function similar to those illustrated in Figure 18) as disclosed, for example, at least with reference to Figures 3-9. The amount of pixel offset required to achieve accuracy at each distance was divided by the generated pixel offset calibration distance, and the results are presented in the scatter plot 1900 as normalized (dimensionless) offset vs. actual distance (mm).As can be seen, calibration is especially effective for achieving the necessary displacement in the far range (e.g., above approximately 500 mm). Figure 20 illustrates example residual accuracy results of the displacement field calibration in the single-point pixel domain illustrated in Figure 19. The accuracy results for the same calibrated sensors illustrated in the 1900 scatter plot of Figure 19 were plotted as accuracy (mm) vs. true distance (mm) in the 2000 scatter plot. As can be seen by comparing the calibrated 2000 scatter plot with the uncalibrated 1600 scatter plot, calibration effectively reduced the maximum error by more than 30 mm. The uncalibrated error exceeded + / -100 mm (beyond the view of the graph), while the calibrated error was within + / -70 mm (at outliers). Furthermore, even though the normalized displacement was more variable at closer distances, as shown in Figure 19, closer distances are less sensitive to calibration map errors (e.g., due to the nature of the relationship, as shown in Figures 15, 16, and 18). Therefore, calibration effectively reduced the error in the near range from approximately + / -16 mm to approximately + / -4 mm (a reduction to approximately 25% of the previous error). Thus, calibration by performing a substantially constant displacement of the transfer function in the position domain (e.g., pixel) profitably improves accuracy. In various modes, calibration by displacement in the position domain of a sensor's transfer function can profitably reduce error within a predetermined accuracy threshold.For example, several zncn Ln / eznz / B / YiAi modalities can usefully provide rapid field calibration to improve and / or restore accuracy by presenting one or more targets at one or more known distances. Figure 21 illustrates a curve fit to an example normalized accuracy error profile for distance sensors after an aging process. In the illustrated example, the magnitude of the accuracy error profile relative to the true distance was normalized for all the uncalibrated sensors illustrated in Figure 16, and the results were plotted on a scatter diagram 2100. In the illustrated example, a second-order polynomial curve fit 2105 was applied to determine a characteristic sensor profile that describes the error. This characteristic (polynomial) profile can then be calibrated for each sensor by determining one or more calibration constants. The calibration constant(s) can, for example, be configured as a coefficient (e.g., a weighting / scaling coefficient) of the function. Therefore, the function can be usefully calibrated to the magnitude of the accuracy error of each sensor at one or more taught distances. In some configurations, this method can usefully provide increased accuracy at taught distances farther from the sensor (e.g., in a long range, such as, by way of example and not limitation, beyond approximately 500 mm). In some configurations, any distance within the sensor's operating range can be used. Figure 22 illustrates example residual accuracy results of a field calibration in the single-point distance domain using the curve fitting illustrated in Figure 21. In example 2200, the uncalibrated sensors illustrated in Figure 16 were calibrated using a distance offset (vs. pixel offset) calibration, for example, as disclosed at least with reference to Figures 9-14. The curve fitting illustrated in Figure 21 was applied, calibrated by a correction factor. For example, a model using a taught distance was employed and curve fitting yielded a formula of the following form: Equation 1: Cd = Te * (A * Dm2+ B * Dm) / (A * Tm2+ B * Tm) Where: • Cd = amount of distance correction • Te = teaching error, accuracy error from teaching at the teaching distance(s) • A = second-order coefficient determined from curve fitting • B = first-order coefficient determined from curve fitting • Dm = uncorrected measured distance zncn Ln / eznz / e / YiAi • Tm = uncorrected measured distance from teaching to the teaching distance. The calibration constant for each sensor can, for example, be defined by: Equation 2: C = Te / (A * Tm2+ B * Tm) The calibration constant can then be applied to determine the correction distance as a function of C and the uncalibrated measured distance Dm by Equation 3: Equation 3: Cd = C * (A * Dm2+ B * Dm) The final corrected distance measurement (De) can then be calculated as follows: Equation 4: De = Dm - Cd In several modalities, distance measurement can be corrected during runtime by calculating Cd on the fly (e.g., as disclosed at least with reference to Figures 9-11), during runtime by applying a correction LUT such as a LUT that maps multiple distances to a corresponding Cd (e.g., as disclosed at least with reference to Figures 12-14), during calibration by generating a corrected LUT that maps multiple positions (e.g., pixel positions) to a corresponding De, or some combination thereof. Although several modes have been described with reference to the figures, other modes are possible. For example, several modes can be configured to be calibrated (in the field) with one or more targets. Each target can, for example, be calibrated at one or more known distances. In several modes that use multiple targets and / or distances for calibration, multiple readings can be averaged, by way of example and not limitation, by taking the median, or otherwise condensed into a single value. Consequently, a substantially constant displacement can be generated. In several modes, calibration can be performed with at least one target at a distance corresponding to a higher accuracy for the specific sensor characteristic(s) and / or configuration. For example, several modes can be configured to perform calibration only if a target is measured as being positioned at a distance of at least 5, 100, 500, 1000, or 10000 mm, or additionally within a range of these values, another appropriate distance threshold, or some combination thereof. In several modes, a minimum target distance and / or a range of target distances can be determined by sensor geometry, environment, electrical and / or mechanical sensor characteristics, or some combination thereof.In several modalities, a placement template (e.g., a length of material of predetermined and / or adjustable length, a goal holder, or a combination thereof) can be provided for quick positioning of a goal at a known distance from the sensor. In various embodiments, a sensor may include, by way of example and not limitation, an optical sensor as described at least with reference to Figures 1, 7 of US application znen Ln / eznz / B / YiAi serial number 17 / 072,028, entitled IMAGE-BASED JAM DETECTION, filed by Wade Oberpriller, et al., on October 15, 2020; with reference to Figures 1, 7 of US application serial number 62 / 916,087, entitled Imaging System Using Triangulation, filed by Wade Oberpriller, et al., on October 16, 2019; and with reference to Figures 1, 7 of U.S. application serial number 62 / 924,020, entitled Imaging System Using Triangulation, filed by Wade Oberpriller, et al., on October 21, 2019, the entire contents of which are incorporated herein by reference.For example, the receiver(s) may be configured as a set of 1-D pixels, as described at least with reference to Figure 1 of the embedded applications. In several modalities, a reflected REMS (e.g., a light signal) at a receiver can result in a profile that is generally bell-shaped or Gaussian (e.g., as disclosed at least with reference to Figure 3B of the applications mentioned above and incorporated herein). The profile may, for example, extend over multiple pixels of a multipixel receiver. Several modalities can determine a centroid of the profile. Several modalities can, for example, interpolate between pixels to determine a centroid position. Consequently, several modalities can profitably digitally reconstruct a centroid location of the REMS with subpixel accuracy. In various modes, a sensor may be configured to detect a distance with reference to a background and / or in the absence of a background. For example, various modes may be configured to detect a jam with reference to a background (e.g., a background mode) and / or in a backgroundless mode. Such modes may, by way of example and not limitation, be configured in accordance with the information disclosed at least with reference to Figures 1-4 of U.S. Provisional Application Serial No. 63 / 158,697, entitled "Non-Contact Motion Detection Sensor Using Distance and Intensity Statistics," filed by Wade Oberpriller et al. on March 9, 2021, the entire contents of which are incorporated herein by reference.Several modes can, for example, be configured for field calibration (e.g., automatically) based on a target at a known distance (e.g., a background in the case of a background mode, a target at a known ratio to a protractor in a backgroundless mode). Therefore, several modes can efficiently calibrate automatically without user intervention. Consequently, several modes can efficiently maintain more accurate readings. Several modes can, for example, calibrate automatically upon activation (e.g., when switched on), based on a predetermined threshold (e.g., time, cycles), as disclosed at least with reference to Figure 2, after and / or before each measurement, through manual input (e.g., remote and / or local user-initiated generation of a calibration start signal), or some combination thereof. Although an example system has been described with reference to the figures, other implementations can be implemented in other industrial, scientific, medical, commercial and / or residential applications. In various configurations, certain implementations of bypass circuits can be controlled in response to signals from analog or digital components, which may be discrete, integrated, or a combination thereof. Such configurations may include programmable devices, programmed devices, or a combination thereof (e.g., PLAs, PLDs, ASICs, microcontrollers, microprocessors), and may include one or more data stores (e.g., cells, registers, blocks, pages) that provide single-level or multi-level digital data storage capacity and may be volatile, non-volatile, or a combination thereof. Some control functions may be implemented in hardware, software, firmware, or a combination thereof. Computer program products may contain a set of instructions that, when executed by a processor device, cause the processor to perform the prescribed functions.These functions can be performed in combination with devices controlled in operational communication with the processor. Computer program products, which may include software, can be stored in a data store tangibly integrated into a storage medium, such as an electronic, magnetic, or rotating storage device, and can be fixed or removable (e.g., hard disk, floppy disk, miniature memory, CD, DVD). Although one example of a system, which may be portable, has been described with reference to the figures above, other implementations can be used in other processing applications, such as desktop computers and networked environments. Temporary auxiliary power inputs can be obtained, for example, from rechargeable or disposable batteries, enabling use in portable or remote applications. Some models can operate via DC voltage sources, such as batteries. Alternating current (AC) inputs, which can be supplied, for example, from a 50 / 60Hz power outlet or a portable generator, can be rectified and appropriately scaled. Provisions for AC inputs (e.g., sine wave, square wave, triangle wave) may include a line-frequency transformer to provide voltage boosting, voltage reduction, and / or isolation. Even though specific features of an architecture have been described, other features can be incorporated to improve performance. For example, caching techniques (e.g., Ll, zncn Ln / eznz / e / YiAi) Layers L2, ...) may be used. Random access memory may be included, for example, to provide a notepad-like memory and / or to load executable code or stored parameter information for use during runtime operations. Other hardware and software may be provided to perform operations such as networking or other communications using one or more protocols, wireless communications (e.g., infrared), stored power supplies and operating power (e.g., batteries), linear switching and / or power supply circuits, software maintenance (e.g., self-testing, upgrades), and the like. One or more communication interfaces may be provided to support data storage and related operations. Some systems can be implemented as a computer system that can be used with various implementations. For example, various implementations can include digital circuitry, analog circuitry, hardware, firmware, computer software, or combinations thereof. Devices can be implemented in a computer program product tangibly embedded in a data carrier, such as a machine-readable storage device, for execution by a programmable processor; and methods can be performed by a programmable processor that executes a program of instructions to perform functions of various modes by operating on input data and generating an output.Several methods can be profitably implemented in one or more computer programs that are executable on a programmable system that includes at least one programmable processor coupled to receive data and instructions from a data storage system and transmit data and instructions to a data storage system, at least one input device, and / or at least one output device. A computer program is a set of instructions that can be used, directly or indirectly, on a computer to perform certain activities or produce a certain result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and can be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. Processors suitable for executing a program of instructions include, for example, both general-purpose and special-purpose microprocessors, which may include a single processor or a multi-processor system of any type of computer. Generally, a processor will receive instructions and data from read-only memory, random-access memory, or both. The essential elements of a computer are a processor to execute instructions and one or more memories to store instructions and data. Generally speaking, a computer will also include, or be operationally coupled to, one or more mass storage devices for storing data files; such devices include magnetic disks, such as internal hard drives and removable disks; magneto-optical disks; and optical disks.Suitable storage devices for the tangible incorporation of computer program instructions and data include all forms of non-volatile memory, including, by way of example, semiconductor memory devices such as EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard drives and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM discs. The processor and memory may be supplemented by ASIO (application-specific integrated circuits) or incorporated into ASICs. In some implementations, each system may be programmed with the same or similar information and / or initialized with substantially identical information stored in volatile and / or non-volatile memory.For example, a data interface can be configured to perform self-configuration, self-download, and / or self-update functions when coupled with an appropriate host device, such as a desktop computer or server. In some implementations, one or more user interface features can be custom-configured to perform specific functions. Various modalities can be implemented on a computer system that includes a graphical user interface and / or an internet browser. To provide user interaction, some implementations can be deployed on a computer that has a display device, such as a CRT (cathode ray tube) or LCD (liquid crystal display) monitor to display information to the user, a keyboard, and a pointing device, such as a mouse or trackball, through which the user can provide input to the computer. In various implementations, the system can communicate using appropriate communication methods, equipment, and techniques. For example, the system can communicate with compatible devices (e.g., devices capable of transferring data to and / or from the system) using point-to-point communication, where a message is transported directly from the source to the receiver over a dedicated physical link (e.g., fiber optic link, point-to-point wiring, daisy chain). System components can exchange information through any form or medium of analog or digital data communication, including packet-based messaging over a communication network.Examples of communication networks include, for instance, a LAN (local area network), a WAN (wide area network), a MAN (metropolitan area network), wireless and / or optical networks, the computers and networks that make up the Internet, or some combination thereof. Other implementations may carry messages by broadcasting to all or substantially all of the devices connected together by a communication network, for example, by using omnidirectional radio frequency (RF) signals. Other implementations may carry messages characterized by high directivity, for example, RF signals transmitted using directional antennas (i.e., narrow beam) or infrared signals that can optionally be used with focusing optics. Still other implementations are possible through the use of appropriate interfaces and protocols such as, by way of example and not limitation, USB 2.0.0, Firewire, ATA / IDE, RS-232, RS-422, RS-485, 802.11 a / b / g, Wi-Fi, Ethernet, IrDA, FDDI (Fiber Distributed Data Interface), token ring networks, frequency division, time division, or code division multiplexing techniques, or some combination thereof. Some implementations may optionally incorporate features such as error checking and correction (ECC) for data integrity, or security measures such as encryption (e.g., WEP) and password protection. In various configurations, the computer system can include Internet of Things (IoT) devices. IoT devices can include objects integrated with electronics, software, sensors, actuators, and network connectivity that allow these objects to collect and exchange data. IoT devices can also be integrated with wired or wireless devices by sending data through an interface to another device. IoT devices can collect useful data and then autonomously route that data among other devices. Various examples of modules can be implemented using circuitry, including various electronic hardware components. By way of example, and not as a limitation, the hardware may include transistors, resistors, capacitors, switches, integrated circuits, other modules, or some combination thereof. In some examples, the modules may include analog logic, digital logic, discrete components, traces, and / or memory circuits fabricated on a silicon substrate that includes various integrated circuits (e.g., FPGA, ASIC), or some combination thereof. In some embodiments, the module(s) may involve the execution of pre-programmed instructions, software executed by a processor, or some combination thereof. For example, some modules may involve both hardware and software. For illustrative purposes, a field-adjustable distance sensor may include an emitter configured to emit an electromagnetic signal. The sensor may include at least one sensing element configured to generate a sensing signal in response to a reflection of the electromagnetic signal; the sensing signal is a function of the electromagnetic signal's position on the at least one sensing element. The sensor may include at least one memory module that includes at least one data store correlating each of multiple measured distances with a corresponding position vector, the correlation being defined by a transfer function. The sensor may include a control circuit configured to perform calibration operations in a teachable mode.Calibration operations may include operating the emitter to launch an initial electromagnetic signal at a target located at a known distance from at least one detection element. Calibration operations may include receiving from at least one detection element an initial detection signal corresponding to a reflection of the initial electromagnetic signal. Calibration operations may include determining an initial position vector based on the initial detection signal. Calibration operations may include receiving a calibration distance signal corresponding to the known distance.Calibration operations may include, if a difference between the known distance and a distance in the data store correlated with the first position vector is greater than a calibration threshold, then generating, based on the calibration distance signal and the first position vector, a calibration constant configured to shift the transfer function by a substantially constant position value. Calibration operations may include determining a second position vector based on the calibration distance signal. These operations may also include comparing the first and second position vectors. The difference between the known distance and the distance stored in the data store may exceed the calibration threshold if the comparison between the first and second position vectors is greater than the calibration threshold. If the comparison is not zero, then a calibration constant can be generated based on this comparison. The calibration constant can be a third position vector. The third position vector can be substantially equal to the difference between the first position vector and the second position vector. Calibration operations may include storing the calibration constant. The control circuit may also be configured to perform, in one run mode, distance measurement operations that include operating the emitter to emit a second electromagnetic signal. These distance measurement operations may include receiving a second detection signal from at least one sensing element, corresponding to a reflection of the second electromagnetic signal. The distance measurement operations may also include determining a measured position vector based on the second detection signal. Finally, the distance measurement operations may include applying a third position vector to the measured position vector to generate a calibrated position vector.Distance measurement operations may include generating a calibrated distance measurement signal by retrieving a distance from the data store that corresponds to the calibrated position vector. Calibration operations may include applying the third position vector to multiple position vectors in the data store to generate a calibrated data store. zncn Ln / eznz / B / YiAi At least one memory module may include a predefined sensor profile. Calibration operations may include determining an expected position vector based on the calibration distance signal. Calibration operations may include generating a first distance signal by determining a distance in the data store that corresponds to the expected position vector. Calibration operations may include generating a second distance signal by determining a distance in the data store that corresponds to the expected position vector. Calibration operations may include comparing the first distance signal and the second distance signal. The difference between the known distance and the distance in the data store may exceed the calibration threshold if the difference between the first distance signal and the second position signal is greater than the calibration threshold.If the comparison is not zero, then the calibration constant can be generated based on the comparison and the default sensor characteristic profile. The default sensor characteristic may include at least one curve-fitting relationship parameter that correlates distance and sensor error. The curve-fitting relationship may be a polynomial function of at least second order. Calibration operations may include storing the calibration constant. The control circuit may be configured to perform distance measurement operations in a run mode. Distance measurement operations may include operating the emitter to emit a second electromagnetic signal. Distance measurement operations may include receiving a second detection signal from at least one sensing element, corresponding to a reflection of the second electromagnetic signal. Distance measurement operations may include determining a measured position vector based on a second detection signal. Distance measurement operations may include generating a measured distance signal by determining a distance in the data store that corresponds to the measured position vector.Distance measurement operations may include applying the calibration constant and the default sensor characteristic profile to the measured position vector to generate a calibrated distance signal. Calibration operations can include generating a correction data store based on the data store, the predefined characteristic profile, and the calibration constant. The correction data store can correlate each of multiple measured distances to a corresponding correction distance. The control circuit can also be configured to perform distance measurement operations in a run mode. Distance measurement operations can include operating the emitter to emit a second electromagnetic signal. Distance measurement operations can include receiving a second detection signal from at least one sensing element, corresponding to a reflection of the second electromagnetic signal. Distance measurement operations can include determining a measured position vector based on the second detection signal.Distance measurement operations can include generating a measured distance signal by determining a distance in the data store that corresponds to the measured position vector. Distance measurement operations can include retrieving a first correction distance from the data store. Distance measurement operations can include generating a calibrated distance signal by applying the first correction distance to the measured distance signal. Calibration operations can include generating a calibrated data store based on the data store, the predefined characteristic profile, and the calibration constant. The calibrated data store can correlate each of multiple position vectors with a corresponding calibrated distance. For illustrative purposes, a field calibration method for a distance sensor may include providing a transmitter configured to emit an electromagnetic signal. The method may also include providing at least one sensing element configured to generate a sensing signal in response to a reflection of the electromagnetic signal. The sensing signal may be a function of the electromagnetic signal's position on the at least one sensing element. The method may also include providing at least one memory module comprising a data store that correlates each of multiple measured distances with a corresponding position vector. The correlation may be defined by a transfer function. Finally, the method may include providing a control circuit configured to perform calibration operations in a teachable mode.Calibration operations may include operating the emitter to launch an initial electromagnetic signal at a target located at a known distance from at least one detection element. Calibration operations may include receiving from at least one detection element an initial detection signal corresponding to a reflection of the initial electromagnetic signal. Calibration operations may include determining an initial position vector based on the initial detection signal. Calibration operations may include receiving a calibration distance signal corresponding to the known distance.Calibration operations may include, if a difference between the known distance and a distance in the data store correlated with the first position vector is greater than a calibration threshold, then generating, based on the calibration distance signal and the first position vector, a calibration constant configured to shift the transfer function by a substantially constant position value. Calibration operations may include determining a second position vector based on the calibration distance signal. These operations may also include comparing the first and second position vectors. The difference between the known distance zncn Ln / eznz / B / YiAi and the distance in the data store may exceed the calibration threshold if the comparison of the first and second position vectors is greater than the calibration threshold. If the comparison is not zero, then the calibration constant can be generated based on the comparison. Calibration operations may include storing the calibration constant. The control circuit may also be configured to perform distance measurement operations in a run mode. Distance measurement operations may include operating the emitter to emit a second electromagnetic signal. Distance measurement operations may include receiving a second detection signal from at least one sensing element, corresponding to a reflection of the second electromagnetic signal. Distance measurement operations may include determining a measured position vector based on the second detection signal. Distance measurement operations may include applying the calibration constant to the measured position vector to generate a calibrated position vector.Distance measurement operations may include generating a calibrated distance measurement signal by retrieving a distance from the data store that corresponds to the calibrated position vector. Calibration operations may include applying the calibration constant to multiple position vectors in the data store to generate a calibrated data store. At least one memory module may include a predefined sensor profile. Calibration operations may include determining an expected position vector based on the calibration distance signal. Calibration operations may include generating a first distance signal by determining a distance in the data store that corresponds to the expected position vector. Calibration operations may include generating a second distance signal by determining a distance in the data store that corresponds to the expected position vector. Calibration operations may include comparing the first distance signal and the second distance signal.The difference between the known distance and the distance in the data store may exceed the calibration threshold if the comparison of the first distance signal and the second position signal is greater than the calibration threshold. If the comparison is not zero, then the calibration constant can be generated based on the comparison and the predefined sensor characteristic profile. Calibration operations may include storing the calibration constant. The control circuit may be configured to perform distance measurement operations in a run mode. Distance measurement operations may include operating the emitter to emit a second electromagnetic signal. Distance measurement operations may include receiving a second detection signal from at least one sensing element, corresponding to a reflection of the second electromagnetic signal. Distance measurement operations may include determining a measured position vector based on the second detection signal. Distance measurement operations may include generating a measured distance signal by determining a distance in the data store that corresponds to the measured position vector.Distance measurement operations may include applying the calibration constant and the default sensor characteristic profile to the measured position vector to generate a calibrated distance signal. Calibration operations may include generating a correction data store based on the data store, the predefined characteristic profile, and the calibration constant. The data store can correlate each of multiple measured distances with a corresponding correction distance. The control circuit may also be configured to perform distance measurement operations in a run mode. Distance measurement operations may include operating the emitter to emit a second electromagnetic signal. Distance measurement operations may include receiving a second detection signal from at least one sensing element, corresponding to a reflection of the second electromagnetic signal. Distance measurement operations may include determining a measured position vector based on the second detection signal.Distance measurement operations may include generating a measured distance signal by determining a distance in the data store that corresponds to the measured position vector. Distance measurement operations may include retrieving a first correction distance from the data store. Distance measurement operations may include generating a calibrated distance signal by applying the first correction distance to the measured distance signal. Calibration operations can include generating a calibrated data store based on the data store, the default characteristic profile, and the calibration constant. The calibrated data store can correlate each of multiple position vectors with a corresponding calibrated distance. Numerous implementations were described. However, it is understood that various modifications may be made. For example, beneficial results may be achieved if the steps of the disclosed techniques are performed in a different sequence, or if the components of the disclosed systems are combined differently, or if the components are supplemented with other components. Therefore, other implementations are contemplated within the scope of the following claims.

Claims

1. A field-adjustable distance sensor, comprising: an emitter configured to launch an electromagnetic signal; at least one detection element configured to generate a detection signal in response to a reflection of the electromagnetic signal, the detection signal being a function of the position of the electromagnetic signal on the at least one detection element; at least one memory module comprising at least one data store that correlates each of a plurality of measured distances with a corresponding position vector, the correlation being defined by a transfer function; and, a control circuit configured to perform, in a teaching mode, calibration operations comprising: operating the emitter to launch a first electromagnetic signal at a target located at a known distance from the at least one detection element;receive from at least one detection element a first detection signal corresponding to a reflection of the first electromagnetic signal; determine a first position vector based on the first detection signal; receive a calibration distance signal corresponding to the known distance; and, if a difference between the known distance and a distance in the data store correlated with the first position vector is greater than a calibration threshold, then generate, based on the calibration distance signal and the first position vector, a calibration constant configured to shift the transfer function by a substantially constant position value.

2. The distance sensor according to claim 1, wherein the calibration operations further comprise: determining a second position vector based on the calibration distance signal; and comparing the first position vector with the second position vector; wherein: the difference between the known distance and the distance in the data store is greater than the calibration threshold if the comparison of the first position vector and the second position vector is greater than the calibration threshold, and, if the comparison is not zero, then the calibration constant is generated based on the comparison.

3. The distance sensor according to claim 2, wherein the calibration constant is a third position vector. zncn Ln / eznz / B / YiAi > tu r\ c N ac* c N 4. The distance sensor according to claim 3, wherein the third position vector is substantially equal to a difference between the first position vector and the second position vector.

5. The distance sensor according to claim 3, wherein: the calibration operations further comprise storing the calibration constant, and the control circuit is further configured to perform, in one execution mode, distance measurement operations comprising: operating the emitter to emit a second electromagnetic signal; receiving from at least one detection element a second detection signal corresponding to a reflection of the second electromagnetic signal; determining a measured position vector based on the second detection signal; applying the third position vector to the measured position vector to generate a calibrated position vector; and generating a calibrated distance measurement signal by retrieving a distance from the data store corresponding to the calibrated position vector.

6. The distance sensor according to claim 3, wherein the calibration operations further comprise applying the third position vector to a plurality of the position vectors in the data store to generate a calibrated data store.

7. The distance sensor according to claim 1, wherein the at least one memory module further comprises a predetermined sensor characteristic profile, and the calibration operations further comprise: determining an expected position vector based on the calibration distance signal; generating a first distance signal by determining a distance in the data store corresponding to the expected position vector; generating a second distance signal by determining a distance in the data store corresponding to the expected position vector;and, compare the first distance signal and the second distance signal, where: the difference between the known distance and the distance in the data store is greater than the calibration threshold if the comparison of the first distance signal and the second position signal is greater than the calibration threshold, and, if the comparison is not zero, then the calibration constant is generated based on the comparison and the default sensor characteristic profile.; 8. The distance sensor according to claim 7, wherein the predetermined sensor feature comprises at least one parameter of a curve fitting relationship that correlates distance with sensor error.

9. The distance sensor according to claim 8, wherein the curve fitting ratio is a polynomial function of at least a second order.

10. The distance sensor according to claim 7, wherein the calibration operations further comprise storing the calibration constant, and the control circuit is further configured to perform, in one execution mode, distance measurement operations comprising: operating the emitter to emit a second electromagnetic signal; receiving from at least one detection element a second detection signal corresponding to a reflection of the second electromagnetic signal; determining a measured position vector based on the second detection signal; generating a measured distance signal by determining a distance in the data store corresponding to the measured position vector; and applying the calibration constant and the predetermined sensor characteristic profile to the measured position vector to generate a calibrated distance signal.

11. The distance sensor according to claim 7, wherein: the calibration operations further comprise generating a correction data store based on the data store, the predetermined characteristic profile, and the calibration constant, wherein the correction data store correlates each of a plurality of measured distances with a corresponding correction distance; the control circuit is further configured to perform, in one execution mode, distance measurement operations comprising: operating the emitter to launch a second electromagnetic signal; receiving from at least one detection element a second detection signal corresponding to a reflection of the second electromagnetic signal; determining a measured position vector based on the second detection signal;zncn Ln / eznz / B / YiAi generate a measured distance signal by determining a distance in the data store that corresponds to the measured position vector; retrieve a first correction distance from the data store; and, generate a calibrated distance signal by applying the first correction distance to the measured distance signal.; 12. The distance sensor according to claim 7, wherein the calibration operations further comprise generating a calibrated data store based on the data store, the predetermined characteristic profile, and the calibration constant, wherein the calibrated data store correlates each of a plurality of position vectors with a corresponding calibrated distance.

13. A method for field calibration of a distance sensor, comprising providing: an emitter configured to launch an electromagnetic signal; at least one detection element configured to generate a detection signal in response to a reflection of the electromagnetic signal, the detection signal being a function of a position of the electromagnetic signal on the at least one detection element; at least one memory module comprising a data store that correlates each of a plurality of measured distances with a corresponding position vector, the correlation being defined by a transfer function; and a control circuit configured to perform, in a teaching mode, calibration operations comprising: operating the emitter to launch a first electromagnetic signal at a target located at a known distance from the at least one detection element;receive from at least one detection element a first detection signal corresponding to a reflection of the first electromagnetic signal; determine a first position vector based on the first detection signal; receive a calibration distance signal corresponding to the known distance; and, if a difference between the known distance and a distance in the data store correlated with the first position vector is greater than a calibration threshold, then generate, based on the calibration distance signal and the first position vector, a calibration constant configured to shift the transfer function by a substantially constant position value.

14. The method according to claim 13, wherein the calibration operations further comprise: determining a second position vector based on the calibration distance signal; and comparing the first position vector and the second position vector; wherein: the difference between the known distance and the distance in the data store is greater than the calibration threshold if the comparison of the first position vector and the second position vector is greater than the calibration threshold, and, if the comparison is not zero, then the calibration constant is generated based on the comparison.

15. The method according to claim 14, wherein: the calibration operations further comprise storing the calibration constant, and the control circuit is further configured to perform, in one execution mode, distance measurement operations comprising: operating the emitter to emit a second electromagnetic signal; receiving from at least one detection element a second detection signal corresponding to a reflection of the second electromagnetic signal; determining a measured position vector based on the second detection signal; applying the calibration constant to the measured position vector to generate a calibrated position vector; and generating a calibrated distance measurement signal by retrieving a distance from the data store corresponding to the calibrated position vector.

16. The method according to claim 14, wherein the calibration operations further comprise applying the calibration constant to a plurality of the position vectors in the data store to generate a calibrated data store.

17. The method according to claim 13, wherein the at least one memory module further comprises a predetermined sensor characteristic profile, and the calibration operations further comprise: determining an expected position vector based on the calibration distance signal; generating a first distance signal by determining a distance in the data store corresponding to the expected position vector; generating a second distance signal by determining a distance in the data store corresponding to the expected position vector;and, compare the first distance signal and the second distance signal, zncn Ln / eznz / B / YiAi κ c N α where: cc* c N the difference between the known distance and the distance in the data store is greater than the calibration threshold if the comparison of the first distance signal with the second position signal is greater than the calibration threshold, and, if the comparison is not zero, then the calibration constant is generated based on the comparison and the default sensor characteristic profile.; 18. The method according to claim 17, wherein the calibration operations further comprise storing the calibration constant, and the control circuit is further configured to perform, in one execution mode, distance measurement operations comprising: operating the emitter to emit a second electromagnetic signal; receiving from at least one detection element a second detection signal corresponding to a reflection of the second electromagnetic signal; determining a measured position vector based on the second detection signal; generating a measured distance signal by determining a distance in the data store corresponding to the measured position vector; and applying the calibration constant and the predetermined sensor characteristic profile to the measured position vector to generate a calibrated distance signal.

19. The method according to claim 17, wherein: the calibration operations further comprise generating a correction data store based on the data store, the predetermined characteristic profile, and the calibration constant, wherein the correction data store correlates each of a plurality of measured distances with a corresponding correction distance; the control circuit is further configured to perform, in one execution mode, distance measurement operations comprising: operating the emitter to emit a second electromagnetic signal; receiving from at least one detection element a second detection signal corresponding to a reflection of the second electromagnetic signal; determining a measured position vector based on the second detection signal; generating a measured distance signal by determining a distance in the data store corresponding to the measured position vector;receive an initial distance correction from the data store; and, generate a calibrated distance signal by applying the initial distance correction to the measured distance signal.

20. The method according to claim 17, wherein the calibration operations further comprise generating a calibrated data store based on the data store, the predetermined characteristic profile, and the calibration constant, wherein the calibrated data store correlates each of a plurality of position vectors with a corresponding calibrated distance.

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