DEVICE FOR DISTANCE MEASUREMENT

Description

[0001] The invention relates to a device for distance measurement and a method for carrying out distance measurements.

[0002] Such devices are generally formed by distance sensors. In particular, such distance sensors can be designed as optical sensors. To perform distance measurements, the distance sensor has a transmitter that emits light beams and a receiver that receives light beams. The distance measurements can be carried out, for example, using a phase measurement method or a pulse-time-of-flight method, whereby in the latter case the transmitter of the distance sensor emits light beams in the form of pulses. In both cases, the unit of light of the transmitted light beams from the distance sensor to the object is measured as the measure of the distance to the object.

[0003] Key requirements for such devices are that they enable the most accurate possible distance measurements, with a particularly fast response time being required, meaning that the device must be able to generate distance measurements in rapid succession.

[0004] This requires appropriately sensitive components, especially receivers and the amplifiers downstream of them. The distance measurements generated in this way are generally subject to measurement noise, which limits the accuracy of the distance measurements.

[0005] In principle, it is known to use suitable filters to improve the quality of distance measurements. Such filters can be designed, for example, as low-pass filters, and in particular as average-value filters. With an average-value filter, the results are calculated by averaging over a large number of distance measurements, which reduces measurement noise.

[0006] In dynamic applications where the distance sensor is moved rapidly relative to the objects being detected, measurement noise is only of minor importance for the accuracy of the determined distance measurements. Rather, in such applications, especially when low-pass or average-value filters are used to filter distance measurements, a lag in the measured distance value compared to the actual distance occurs.

[0007] In YU XIANG ET AL: "Multi-sensor Fusion Height Prediction Algorithm Based on Kalman Filtering", 2019 CHINESE CONTROL CONFERENCE (CCC), TECHNICAL COMMITTEE ON CONTROL THEORY, CHINESE ASSOCIATION OF AUTOMATION, July 27, 2019 (2019-07-27), pages 3016-3022, XP033635399, a system for determining the altitude of an unmanned aerial system is described. This system comprises a laser-based distance sensor, an accelerometer, and a barometer. The measured values ​​from these sensors are processed using a Kalman filter to determine the altitude.

[0008] In ARIANTE GENNARO ET AL: "UAS for positioning and field mapping using LIDAR and IMU sensors data: Kalman filtering and integration", 2019 IEEE 5TH INTERNATIONAL WORKSHOP ON METROLOGY FOR AEROSPACE (METROAEROSPACE), IEEE, June 19, 2019 (2019-06-19), pages 522-527, XP033634032, an unknown flight system is described. For positioning the flight system, measurements from an accelerometer and a LIDAR sensor are evaluated. The accelerometer measurements are filtered using a Kalman filter.

[0009] The invention is based on the objective of providing a device and a method which enable accurate distance measurements under different operating conditions.

[0010] The features of the independent claims are provided to solve this problem. Advantageous embodiments and expedient further developments of the invention are described in the dependent claims.

[0011] The invention relates to a device comprising a distance sensor and an acceleration sensor, wherein distance signals d(K-T1) are generated by the distance sensor in a clock cycle T1 and acceleration signals b(K·T2) are generated by the acceleration sensor in a clock cycle T2, and comprising a fusion unit configured to generate noise-reduced distance measurements D(K·T3) in a clock cycle T3, in which the simultaneously determined distance signals d(K-T1) and acceleration signals b(K-T2) are combined. At least one filter is provided by means of which the distance signals d(K-T1) and the acceleration signals b(K-T2) are brought to a common clock cycle T3 and then combined with the clock cycle T3 to form the noise-reduced distance measurements D(K·T3). All clock cycles T1, T2, and T3 are distinct.

[0012] The invention further relates to a method for carrying out distance measurements.

[0013] According to the invention, all clock signals T1, T2, and T3 are different. Accordingly, distance signals d(K-T1) are generated in the distance sensor using a clock signal T1 that differs from the clock signal T2 of the acceleration signals b(K-T2) of the acceleration sensor. At least one filter is provided by means of which the distance signals d(K-T1) and the acceleration signals b(K-T2) are brought to a common clock signal T3 and then combined with the clock signal T3 to form the noise-reduced distance measurements D(K·T3).

[0014] In particular, the filter is an interpolation filter.

[0015] By additionally using an accelerometer and fusion, i.e., the time-synchronous linking of the acceleration signals of this accelerometer with the distance signal of the distance sensor, the accuracy of the distance measurements is significantly increased in a surprisingly simple way for both static and dynamic applications; that is, high measurement accuracy is achieved regardless of whether the device is stationary, moving slowly, or moving at high speed relative to the objects being detected.

[0016] The fusion unit used to fuse the distance and acceleration signals is designed as a filter unit. In principle, this filter unit can be a mean-value filter. A Kalman filter is particularly advantageous.

[0017] The fusion process according to the invention significantly reduces measurement noise at low speeds between the device and the object being detected. At high relative speeds between the device and the object being detected, it prevents lag in distance measurements, thereby achieving high accuracy and temporal dynamics in distance measurements.

[0018] The device according to the invention can therefore be used in both static and dynamic applications. An example of a static application is a stationary device that performs distance measurements against a defined, existing measuring object. An example of a dynamic application is a device mounted on a vehicle, which, for example, performs distance measurements against a stationary measuring object. The distance measurements against the measuring object can be used, in particular, for position monitoring.

[0019] Advantageously, the device according to the invention can also be used for positioning tasks.

[0020] According to an advantageous embodiment of the invention, the distance sensor of the device according to the invention is designed as an optical sensor. This sensor comprises a transmitter emitting light beams and a receiver receiving light beams. In principle, distance measurements can be carried out with this optical sensor using a triangulation method. Particularly advantageously, the distance measurements are performed using a pulse-time-of-flight method or a phase-measurement method. In this case, the distance sensor can also be designed as a radar sensor or the like.

[0021] According to a structurally advantageous embodiment of the device according to the invention, its components are arranged in a housing.

[0022] The device thus forms a compact unit.

[0023] Advantageously, the device features a control and evaluation unit that serves, on the one hand, to control the sensor components, in particular the transmitter. Furthermore, this unit is used to evaluate received signals from the receiver.

[0024] The invention will be explained below with reference to the drawings. The drawings show: Figure 1: Schematic representation of an embodiment of the device according to the invention. Figure 2: Arrangement of the device on a vehicle. Figure 3: Time diagram of distance values ​​during the vehicle's journey for the arrangement according to the invention. Figure 2 Figure 4: Results of the measurement filtering for the device according to the invention when the vehicle is stationary. Figure 5: Time-dependent distance values ​​at high vehicle speed.

[0025] Figure 1 Figure 1 shows an embodiment of the device 1 according to the invention. The components of the device 1 are integrated in a housing 2.

[0026] The device 1 comprises a distance sensor 3 designed as an optical sensor. This distance sensor 3 has a transmitter 5 emitting light beams 4 and a receiver 7 receiving light beams 6. The transmitter 5 can be a laser diode, and the receiver 7 a photodiode. In this case, distance measurements are performed with the distance sensor 3 using a pulse-time-of-flight method. For this purpose, the transmitter 5 emits light beams 4 in the form of light pulses. To determine the distance of an object 8 to the device 1, the time of flight of the light pulses from the transmitter 5 back to the receiver 7 is evaluated. A computing unit (not shown) can be assigned to the receiver 7 for this purpose.

[0027] Furthermore, the device 1 includes an acceleration sensor 9, which is preferably able to detect accelerations in all three spatial directions.

[0028] The distance sensor 3 generates distance signals d(K·T), where k = 1, 2, 3, ..., within a predetermined clock cycle T. At the same clock cycle T, the acceleration sensor 9 can generate acceleration signals b(K·T), where k = 1, 2, 3, ..... However, according to the invention, the clock cycles for the distance signals and the acceleration signals are different.

[0029] According to the invention, the distance sensors 3 d(K·T) and acceleration sensors 9 b(K·T) are fed to a fusion unit 10 in the form of a filter unit. There, the distance signals and acceleration signals are fused in such a way that the respective signals d(K·T) and b(K·T) are combined.

[0030] The filter unit is preferably designed as a Kalman filter. Alternatively, the filter unit can be a mean-value filter.

[0031] At output 12 of the fusion unit 10, filtered distance measurements D(K·T) are obtained and fed to a control and evaluation unit 11, which is a processor or similar device. The control and evaluation unit 11 serves to control the sensor components, namely the distance sensor 3 and the acceleration sensor 9. Furthermore, an object detection signal is generated based on the determined distance measurements and output via output 12. The object detection signal can be directly derived from a distance value or from it. For example, it can indicate when a detectable object 8 is detected at a target position. Such object detection signals can be used, in particular, for positioning tasks.

[0032] Figure 2 shows an application for device 1 according to Figure 1The device 1 is mounted on a vehicle 13, which can travel on a roadway 14 at a speed v(t). The distance sensor 3 of the device 1 continuously determines the distance between the device 1, and thus the vehicle 13, and a stationary measuring object 15.

[0033] Figure 3 qualitatively shows the time dependence of distance values ​​determined with the device 1 for currently determined distances to the measuring object 15 when the vehicle 13 moves away from the object 8.

[0034] In area I, vehicle 13 moves at approximately a constant speed. In area II, vehicle 13 has come to a standstill.

[0035] When the vehicle 13 (area II) is stationary, the filter unit reduces the measurement noise in the distance signals by fusing them with the acceleration signals.

[0036] Figure 4Figure II shows the results of filtering. The ideal distance values ​​are denoted by a. The noisy distance signals d(K·T) are denoted by b. The distance measurements D(K·T) filtered by fusion unit 10 are denoted by c, assuming fusion unit 10 is a mean-value filter. The distance measurements D(K·T) obtained by filtering with fusion unit 10 configured as a Kalman filter are denoted by d.

[0037] How Figure 4 This shows that filtering with the Kalman filter delivers better, i.e., less noisy, distance measurements than filtering with a mean value filter.

[0038] Figure 5 shows the results of filtering distance signals in range 1, where the labels a, b, c, d of the individual measured values ​​correspond to the labels a, b, c, d according to Figure 4 are equivalent to.

[0039] How Figure 5This shows that when the distance signals d(K·T) are filtered with a mean value filter, an offset of the filtered distance measurements to the ideal distance values ​​is obtained, while the distance measurements filtered with a Kalman filter correspond almost to the ideal distance values. Reference symbol list

[0040] (1) Device (2) Housing (3) Distance sensor (4) Transmitting light beam (5) Transmitter (6) Receiving light beam (7) Receiver (8) Object (9) Accelerometer (10) Fusion unit (11) Control and evaluation unit (12) Output (13) Vehicle (14) Roadway (15) Object being measured

Claims

1. Device (1) for measuring distance comprising a distance sensor (3) and an acceleration sensor (9), wherein distance signals d(K-T1) are generated in a cycle T1 using the distance sensor (3) and acceleration signals b(K-T2) are generated in a cycle T2 using the acceleration sensor (9) are generated, and comprising a fusion unit (10) which is configured to generate noise-reduced distance measurement values D(K-T3) in a clock cycle T3, in which the distance signals d(K-T1) and the acceleration signals b(K-T2) are combined, characterised in that at least one filter is provided, by means of which the distance signals d(K-T1) and the acceleration signals b(K-T2) are synchronised to a common clock T3 and are then combined with the clock T3 to form the noise-reduced distance measurement values D(K-T3), wherein all clocks T1, T2, T3 are different.

2. Device (1) according to claim 1, characterised in that the fusion unit (10) is a filter unit.

3. Device (1) according to claim 2, characterised in that the filter unit is a state-space filter.

4. Device (1) according to claim 3, characterised in that the filter unit is a Kalman filter.

5. Device (1) according to one of claims 1 to 4, characterised in that the filter by means of which the distance signals d(K-T1) and the acceleration signals b(K-T2) are synchronised to a common clock T3 is an interpolation filter.

6. Device (1) according to one of claims 1 to 5, characterised in that the distance sensor (3) is an optical sensor.

7. Device (1) according to one of claims 1 to 6, characterised in that a distance sensor (3) operating according to a pulse-time-of-flight method, a phase measurement method or a triangulation method is provided.

8. Device (1) according to any one of claims 1 to 7, characterised in that its components are arranged in a housing (2).

9. Device (1) according to any one of claims 1 to 8, characterised in that it comprises a control and evaluation unit (11).

10. Method for performing distance measurements using a device (1) comprising a distance sensor (3) and an acceleration sensor (9), wherein distance signals d(K-T1) are generated in a cycle T1 by the distance sensor (3) and acceleration signals b(K-T2) are generated in a cycle T2 by the acceleration sensor (9) in a cycle T2, and comprising a fusion unit (10) which is configured to generate noise-reduced distance measurement values D(K-T3) in a cycle T3, in which the distance signals d(K-T1) and the acceleration signals b(K-T2) are combined, characterised in that at least one filter is provided, by means of which the distance signals d(K-T1) and the acceleration signals b(K-T2) are synchronised to a common clock T3 and are then combined with the clock T3 to form the noise-reduced distance measurement values D(K-T3), wherein all clocks T1, T2, T3 are different.

11. A method according to claim 10, characterised in that the device (1) is used in a static measurement arrangement.

12. A method according to claim 10, characterised in that the device (1) is used in a dynamic measurement arrangement.

13. A method according to any one of claims 10 to 12, characterised in that the distance measurement values generated by the device (1) are used for positioning.