WO2020142939A1 - 回波信号处理方法、设备及存储介质 - Google Patents

回波信号处理方法、设备及存储介质 Download PDF

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Publication number
WO2020142939A1
WO2020142939A1 PCT/CN2019/071018 CN2019071018W WO2020142939A1 WO 2020142939 A1 WO2020142939 A1 WO 2020142939A1 CN 2019071018 W CN2019071018 W CN 2019071018W WO 2020142939 A1 WO2020142939 A1 WO 2020142939A1
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Prior art keywords
echo signal
noise
energy characteristic
echo
characteristic parameter
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English (en)
French (fr)
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许友
陈涵
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SZ DJI Technology Co Ltd
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SZ DJI Technology Co Ltd
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Priority to PCT/CN2019/071018 priority Critical patent/WO2020142939A1/zh
Priority to CN201980005477.XA priority patent/CN111670379A/zh
Publication of WO2020142939A1 publication Critical patent/WO2020142939A1/zh
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/486—Receivers
    • G01S7/487—Extracting wanted echo signals, e.g. pulse detection

Definitions

  • Embodiments of the present invention relate to the field of radar, and in particular, to an echo signal processing method, device, and storage medium.
  • mobile platforms such as vehicles, drones, and mobile robots
  • laser detection equipment such as lidar
  • targets such as obstacles
  • the lidar Normally, there are interference noises in the environment where the lidar is located, such as dust, rain, fog, haze, snow and other objects.
  • the lidar emits an optical pulse signal, and the optical pulse signal will encounter the target and interference noise, causing the laser detection device to receive multiple echo signals, where the multiple echo signals include interference noise (i.e. Reflection), ie noise echo signal.
  • Noise echo signals will affect Lidar's accurate detection of targets.
  • Embodiments of the present invention provide an echo signal processing method, device, system, and storage medium to improve the accuracy of noise echo signal recognition, and thereby improve the accuracy of target detection by laser detection equipment.
  • a first aspect of the embodiments of the present invention is to provide an echo signal processing method, which is applied to a laser detection device, and is characterized by including:
  • Emitting optical pulses and acquiring multiple echo signals corresponding to the optical pulses
  • each echo signal is a noise echo signal generated by interference noise.
  • a second aspect of the embodiments of the present invention is to provide a laser detection device, which includes: a laser transmitter, a receiver, and a processor;
  • the laser is used to emit light pulses
  • the receiver is used to obtain multiple echo signals corresponding to the optical pulse
  • the processor is used to:
  • each echo signal is a noise echo signal generated by interference noise.
  • a third aspect of the embodiments of the present invention is to provide a movable platform, including:
  • the power system is installed on the body to provide power
  • a fourth aspect of the embodiments of the present invention is to provide a computer-readable storage medium on which a computer program is stored, which is executed by a processor to implement the echo signal processing method described in the first aspect.
  • the echo signal processing method, device and storage medium provided in this embodiment determine the energy characteristic parameter and distance of each echo signal in the multiple echo signals by acquiring multiple echo signals corresponding to the optical pulses According to the energy characteristic parameters and distance data of each echo signal, it is determined whether each echo signal is a noise echo signal generated by interference noise. In this way, it is possible to accurately determine the noise echo signal generated by the interference noise among the multiple echo signals currently collected, which can effectively improve the accuracy of the detection target of the laser detection device, providing safe movement of the movable platform Foundation.
  • FIG. 1 is a structural diagram of a laser detection device provided by an embodiment of the present invention.
  • 3 is a schematic diagram of the relationship between the echo energy of an echo signal generated by an object with different reflectances and the distance data of the echo signal according to an embodiment of the present invention
  • FIG. 4 is a schematic diagram of the relationship between the pulse width of the rain fog and dust echo signals and the distance data of the echo signals provided by the embodiment of the present invention
  • FIG. 5 is a distance distribution diagram between an interference noise generating an echo signal and a laser detection device according to an embodiment of the present invention
  • FIG. 6 is a structural diagram of a laser detection device provided by an embodiment of the present invention.
  • FIG. 7 is a structural diagram of a movable platform provided by an embodiment of the present invention.
  • a component when a component is said to be “fixed” to another component, it can be directly on another component or there can be a centered component. When a component is considered to be “connected” to another component, it can be directly connected to another component or there may be a centered component at the same time.
  • FIG. 1 is a schematic structural diagram of a laser detection device provided in an embodiment of the present invention.
  • the lidar may include a laser 101, a lens 102, a controller 103, a first motor 104, a second motor 105, a first prism 106, a second prism 107, a beam splitter 108, a receiver 109 and A Time of Flight (TOF) module 110, where the receiver 109 includes a photodiode, for example, may be an Avalanche Photodiode (APD).
  • APD Avalanche Photodiode
  • the laser of the lidar turns the electrical pulse signal into a divergent light pulse signal
  • the lens converts the divergent light pulse signal into a parallel light pulse signal
  • the controller set at In the chip
  • the first motor is used to control the rotation of the first prism
  • the second motor is used to control the rotation of the second prism
  • the differential rotation of the first prism and the second prism is used to change the light emitted through the first prism and the second prism
  • the direction of the pulse signal After the emitted optical pulse signal meets the target, it will be reflected back to the optical pulse signal.
  • the reflected optical pulse signal is the echo signal.
  • the echo signal is split by the beam splitter and enters the receiving In the receiver (including APD), the receiver converts the echo signal into an electrical pulse signal, and calculates the distance between the lidar and the target through TOF (set in the chip), and then generates points based on the distance between the lidar and the target Cloud data.
  • the lidar Generally, there are interference noises in the environment where the lidar is located, such as dust, rain, haze, snow and other objects.
  • the lidar emits an optical pulse signal, and the optical pulse signal will encounter the target and interference noise, causing the laser detection device to receive multiple echo signals, where the multiple echo signals include interference noise (i.e. Reflection), ie noise echo signal.
  • the noise echo signal will affect the accurate detection of the target by the lidar, and the noise echo signal needs to be filtered out.
  • the first echo signal among the multiple echo signals is determined as the effective echo signal or the one echo signal with the largest energy among the multiple echo signals is determined as the effective echo, and the other echo signals are determined.
  • the wave signal is determined as a noise echo signal.
  • this method is not accurate, and it is very likely that the echo signal generated by a distant target is determined as a noise echo signal, that is, a distant target is determined as interference noise.
  • the present invention provides an echo signal processing method, device and storage medium.
  • FIG. 2 is a schematic flowchart of an echo signal processing method according to Embodiment 1 of the present invention.
  • the noise echo signal processing method is applied to a laser detection device. As shown in FIG. 2, the method includes:
  • Step 201 Transmit an optical pulse signal and obtain multiple echo signals corresponding to the optical pulse;
  • the laser detection device includes a laser and a receiver.
  • the laser may emit an optical pulse signal, and the optical pulse signal encounters a target and/or interference noise will generate reflection to generate multiple echo signals, and the receiver may receive multiple echo signals corresponding to the optical pulse.
  • Step 202 Determine energy characteristic parameters and distance data of each echo signal in the plurality of echo signals
  • the laser detection device may include a processor, where the processor may include one or more.
  • the processor may determine the energy characteristic parameter corresponding to each of the plurality of echo signals received by the receiver according to.
  • the energy characteristic parameter may include any information that can indicate the energy characteristic parameter, and the energy characteristic parameter is determined according to at least one of echo energy, pulse width, height, and area of the echo signal. Further, the energy characteristic parameter may include at least one of echo energy, pulse width, height, and area of the echo signal.
  • the processor may also calculate distance data corresponding to each echo signal according to the TOF as described above, where the distance data may be distance data between the laser detection device and the object that generates the echo signal.
  • Step 203 Determine whether each echo signal is a noise echo signal generated by interference noise according to energy characteristic parameters and distance data of each echo signal.
  • the energy characteristic parameters and distance data of each echo signal determines whether the echo signal is a noise echo signal generated by interference noise, that is, according to each The energy characteristic parameters and distance data of an echo signal filter out the noise echo signals in multiple echo signals.
  • the echo signal processing method provided in this embodiment determines the energy characteristic parameters and distance data of each echo signal in the multiple echo signals by acquiring multiple echo signals corresponding to the optical pulses, and according to each The energy characteristic parameters and distance data of the echo signal determine whether each echo signal is a noise echo signal generated by interference noise. In this way, it is possible to accurately determine the noise echo signal generated by the interference noise among the multiple echo signals currently collected, which can effectively improve the accuracy of the detection target of the laser detection device, providing safe movement of the movable platform Foundation.
  • the determining whether each of the echo signals is a noise echo signal according to the energy characteristic parameter and the distance data of each echo signal includes: determining according to the distance data of each echo signal A reference energy characteristic parameter of each echo signal; determining whether each echo signal is a noise echo signal according to the energy characteristic parameter and the reference energy characteristic parameter of each echo signal.
  • the laser detection device may determine the reference energy characteristic parameter corresponding to each echo signal according to the distance data of each echo signal , wherein the reference energy characteristic parameter may be used to indicate the energy characteristic parameter of the echo signal generated by the interference noise when the interference noise is at the distance indicated by the distance data.
  • the energy characteristic parameter of each echo signal and the reference energy characteristic parameter may be used to determine the relationship between the echo energy characteristic parameter and the corresponding reference energy reference information. Relationship, determining whether each of the echo signals is a noise echo signal according to the relationship.
  • the determining whether each of the echo signals is a noise echo signal according to the energy characteristic parameter of each echo signal and the reference energy characteristic parameter includes: when the energy characteristic parameter of the echo signal is less than the When the reference energy characteristic parameter of the echo signal is determined, the echo signal is determined to be a noise echo signal.
  • the energy characteristic parameter of the echo signal is the echo energy of the echo signal
  • the characteristic information of the reference energy is the reference echo energy as an example for description.
  • the echo energy of the echo signal received by the receiver of the lidar detection device is mainly determined by the distance data of the echo signal and the reflectance of the object that generates the echo signal, for example:
  • E intensity is the echo energy of the echo signal
  • r is the reflectivity of the object generating the echo signal
  • R is the distance data of the echo signal
  • k is the scale factor
  • objects with different reflectances have the following relationship curve between echo energy and distance data.
  • the echo energy is positively correlated with the reflectivity of the object and negatively correlated with the square of the distance indicated by the distance data.
  • the greater the reflectivity of the object the echo of the echo signal generated by the object The greater the energy.
  • the reflectivity of the interference noise is very low compared to the reflectivity of the target.
  • the reflectivity of the interference noise is generally lower than a preset reflectivity threshold, such as 3.2 in the figure.
  • Objects smaller than the preset reflectivity threshold can be regarded as interference noise.
  • a preset reflectivity threshold of 3.2 is taken as an example for description.
  • the detection device may determine the reference echo energy corresponding to the distance data according to the distance data of each echo signal, when the echo signal When the echo energy is less than the reference echo energy, it can be determined that the echo signal is an echo signal generated by interference noise.
  • the energy characteristic parameter of the echo signal is the pulse width of the echo signal
  • the reference energy characteristic parameter is the reference pulse width as an example for description.
  • Pw is the pulse width of the echo signal
  • k is the scale factor
  • r is the reflectivity
  • R is the detection distance of the radar
  • g -1 is the conversion function.
  • the pulse width of the echo signal is positively correlated with the reflectivity of the object and negatively correlated with the square of the distance indicated by the distance data.
  • the greater the reflectance of the object the object produces The greater the pulse width of the echo signal.
  • the reflectivity of the interference noise is very low compared to the reflectivity of the target.
  • the reflectivity of the interference noise is generally lower than a preset reflectivity threshold.
  • the preset reflectivity threshold can be It is the reflectivity of rain fog or dust. Objects with reflectivity less than the preset reflectivity threshold can be regarded as interference noise. Referring to FIG. 4, FIG.
  • the pulse width corresponding to each distance data on the filtering curve of rain and mist or the filtering curve of dust is the reference pulse width corresponding to the distance data, wherein the reference pulse width may be used to indicate that interference noise is at the distance
  • the pulse width of the echo signal generated by the interference noise at the distance indicated by the data is the reference pulse width corresponding to the distance data, wherein the reference pulse width may be used to indicate that interference noise is at the distance
  • the detection device may determine the reference pulse width corresponding to the distance data according to the distance data of each echo signal, when the pulse width of the echo signal When it is smaller than the reference pulse width, it can be determined that the echo signal is an echo signal generated by interference noise.
  • the laser detection device can compare the magnitude relationship between the energy characteristic parameter and the reference energy characteristic parameter, when the energy characteristic of the echo signal When the parameter is less than the reference energy characteristic parameter of the echo signal, it is determined that the echo signal is a noise echo signal.
  • the determining whether each of the echo signals is a noise echo signal according to the energy characteristic parameter of each echo signal and the reference energy characteristic parameter includes: when the energy characteristic parameter of the echo signal is greater than the When the reference energy characteristic parameter of the echo signal is determined, the echo signal is determined to be an effective echo signal, that is, the echo signal is determined to be the echo signal generated by the target.
  • the determining the reference energy characteristic parameter of each echo signal according to the distance data of each echo signal includes: substituting the distance data of the echo signal into a noise echo filtering curve To determine the reference energy characteristic parameter of the echo signal.
  • the lidar detection device may substitute the distance data into a noise echo filtering curve, where the noise echo filtering curve is used to indicate the reflectivity of the interference noise,
  • the method described above can be used to determine whether the echo signal is a noise echo generated by interference noise according to the energy characteristic parameter of the echo signal and the reference energy characteristic parameter signal.
  • the noise-echo filtering curve is based on the reflectivity of the interference noise, the energy characteristic parameters of the multiple echo signals generated by the interference noise, and the energy characteristic parameters corresponding to the multiple echo signals Calibration of multiple distance data.
  • the pulse width and distance data corresponding to the pulse width of the multiple echo signals generated by the interference noise can be obtained, wherein the pulse width and the The distance data corresponding to the pulse width constitutes multiple position points as shown in FIG.
  • the noise echo filtering curve is selected according to the type of interference noise specified by the user.
  • the noise echo filtering curve may be stored in the storage device of the lidar detection device, and in some cases, the noise echo filtering curve may include multiple types.
  • the dust filtering curve or the rain mist filtering curve shown in FIG. 4. The user can select the corresponding noise filter curve according to the environment of the laser detection device. For example, when the laser detection device is used in a rain and fog environment, the user can select the rain and fog filtering curve as shown in FIG. 4; when the laser detection device is used in an environment with more gray layers, the user can select the one shown in FIG. 4 Dust filter curve.
  • the noise echo filtering curve may be selected by the laser detection device according to the identified environment type.
  • the laser detection device can identify the type of environment in which the laser detection device is located, for example, whether the laser detection device is in a rain or fog environment or a dust environment, and select different types of noise echo filtering according to the identified environment type Curve, for example, when it is recognized that the laser detection device is in a rain and mist environment, the rain and mist filtering curve shown in FIG. 4 is selected, and when it is recognized that the laser detection device is in a dust environment, the dust filtering curve as shown in FIG. 4 is selected.
  • determining that the echo signal is a noisy echo signal includes: when the echo signal When the energy characteristic parameter of is less than the reference energy characteristic parameter of the echo signal, determine whether the distance data of the echo signal is less than the reference distance data; if so, determine that the echo signal is a noise echo signal .
  • the laser detection device determines that the energy characteristic parameter of the echo signal is less than the reference energy characteristic parameter of the echo signal, it may perform further judgment. For example, considering that the interference noise is generally a tiny particulate object in the environment, the probability that the laser detection device receives the echo signal generated by the interference noise located far away is relatively small. Therefore, the distance data of the echo signal can be further compared with a reference distance threshold to determine whether the distance data of the echo signal is less than the reference distance data, and if so, the echo signal is determined to be a noise echo signal, If not, it is determined that the echo signal is a valid echo signal.
  • the reference distance data is determined according to the distance distribution between the interference noise generating the noise echo signal and the laser detection device.
  • the distance between the interference noise generating the noise echo signal and the laser detection device may obey a specific distance distribution, for example, the distance distribution is a Poisson distribution or a Gaussian distribution.
  • the distance distribution between the interference noise generating the noise echo signal and the laser detection device as a Poisson distribution for example, that is, the distance between the interference noise generating the noise echo signal and the laser detection device Obey the following distribution:
  • the ⁇ takes different values. For example, if the interference noise is rain and fog, the ⁇ can be selected as 3.5, so that the interference noise generated by the interference noise as shown in FIG. 5 can be obtained
  • the distance distribution diagram of the interference noise of the signal and the laser detection device Observing the distance distribution diagram, it can be seen that the interference noise is mainly distributed within a range of 10 meters from the laser detection device.
  • a reference distance threshold may be determined according to the distance distribution, for example, the reference distance threshold may be 10 meters, and it is determined whether the distance data of the echo signal is less than 10 meters; if it is, the echo signal is determined to be Noise echo signal. If not, it can be determined that the echo signal is a valid echo signal.
  • the type of the distance distribution may be determined according to the type of interference noise specified by the user.
  • the distance of the noise echo signal generated by different types of interference noise may obey different types of distance distribution, and the different types of distance distribution may make the reference distance data different.
  • the distance data of the echo signal generated by rain and fog may follow Poisson distribution
  • the distance data of the echo signal generated by dust may follow Gaussian distribution.
  • the laser detection device may determine the distance distribution of the type corresponding to the type of interference noise according to the type of interference noise specified by the user.
  • one or more parameters in the distance distribution are determined according to the type of interference noise specified by the user.
  • the parameters in the distance distribution between different types of interference noise and the laser detection device may be different. Different parameters may make the reference distance data different.
  • One or more parameters in the distance distribution are Determined according to the type of interference noise specified by the user. For example, the distance distribution between the rain fog generating the noise echo signal and the laser detection device and the distance distribution between the dust generating the noise echo signal and the laser detection device are both Poisson distribution, and the rain and fog correspond to The parameter ⁇ in the Poisson distribution may be different from the parameter ⁇ in the Poisson distribution corresponding to dust.
  • the laser detection device may determine one or more parameters in the distance distribution of the type corresponding to the type of interference noise according to the type of interference noise specified by the user. For example, the laser detection device may determine the parameter ⁇ in the Poisson distribution according to the type of interference noise selected by the user.
  • determining that the echo signal is a noisy echo signal includes: when the echo signal When the energy characteristic parameter of is less than the reference energy characteristic parameter of the echo signal, the distance data is determined according to the distance data and the distance distribution between the interference noise generating the noise echo and the laser detection device Probability; when it is determined whether the probability is greater than a preset probability threshold, when yes, the echo signal is determined to be a noise echo signal, and when not, the echo signal is determined to be an effective echo signal.
  • the laser detection device determines that the energy characteristic parameter of the echo signal is less than the reference energy characteristic parameter of the echo signal, it may perform further judgment.
  • the interference noise is generally a tiny particle object in the environment
  • the probability that the laser detection device receives the echo signal generated by the interference noise located at a distance is relatively small. Therefore, the probability corresponding to the distance data can be further determined according to the distance data and the distance distribution between the interference noise generating the noise echo and the laser detection device.
  • the theoretical analysis shows that the distance between the interference noise generating the noise echo signal and the laser detection device may follow a specific distance distribution, for example, the distance distribution follows the Poisson distribution or Gaussian distribution .
  • the distance between the interference noise generating the noise echo signal and the laser detection device Obey the following distribution:
  • the ⁇ takes different values.
  • the ⁇ can be selected as 3.5, so that the interference noise generated by the interference noise as shown in FIG. 5 can be obtained
  • the distance distribution diagram of the interference noise of the signal and the laser detection device As can be seen from Figure 5, when the distance data of the echo signal generated by the interference noise is in the range of 0-10 meters, the probability of the distance data in the Poisson distribution is large, indicating that the interference noise is mainly distributed in the range of 1-10 meters When the distance of the echo signal generated by the interference noise is within 10 meters of the distance data, the probability of the distance data in the Poisson distribution is very small, indicating that the interference noise is unlikely to be distributed within the range of 10 meters.
  • the laser detection device can determine the probability corresponding to the distance data according to the distance data and the distance distribution (eg Poisson distribution) between the interference noise generating the noise echo and the laser detection device, wherein the distance data
  • the corresponding probability may include a probability corresponding to a distance area of the distance data, and the size of the distance area may be selected by a person skilled in the art according to requirements.
  • a preset probability threshold for example, 0.2 or 0.25, etc.
  • the type of the distance distribution may be determined according to the type of interference noise specified by the user.
  • the distances of the noise echo signals generated by different types of interference noise may obey different types of distance distributions, and the different types of distance distributions may make the preset probability thresholds different.
  • the distance data of the echo signal generated by rain and fog may follow Poisson distribution
  • the distance data of the echo signal generated by dust may follow Gaussian distribution.
  • the laser detection device may determine the distance distribution of the type corresponding to the type of interference noise according to the type of interference noise specified by the user.
  • one or more parameters in the distance distribution are determined according to the type of interference noise specified by the user.
  • the parameters in the distance distribution between different types of interference noise and the laser detection device may be different. Different parameters may make the preset probability thresholds different, and one or more in the distance distribution
  • the parameters are determined according to the type of interference noise specified by the user. For example, the distance distribution between the rain and fog generating the noise echo signal and the laser detection device and the distance distribution between the dust generating the noise echo signal and the laser detection device are subject to the Poisson distribution, and the rain and fog correspond to The parameter ⁇ in the Poisson distribution may be different from the parameter ⁇ in the Poisson distribution corresponding to dust.
  • the laser detection device may determine the distance distribution of the type corresponding to the type of interference noise according to the type of interference noise specified by the user.
  • the laser detection device can determine the parameter ⁇ in the Poisson distribution according to the type of interference noise selected by the user.
  • the method further includes: filtering the noise echo signal when it is determined that the echo signal is a noise echo signal.
  • the movable platform 600 includes: a laser 601, a receiver 602, and a processor 603, where,
  • the laser 601 is used to emit light pulses
  • the receiver 602 is configured to acquire multiple echo signals corresponding to the optical pulse
  • the processor 603 is used to:
  • each echo signal is a noise echo signal generated by interference noise.
  • the energy characteristic parameter is determined according to at least one of echo energy, pulse width, height, and area of the echo signal.
  • each echo signal is a noise echo signal according to the energy characteristic parameter and distance data of each echo signal, it is specifically used to:
  • the reference energy characteristic parameter of each echo signal is determined according to the distance data of each echo signal, where the reference energy characteristic parameter can be used to indicate that the interference noise is caused by the distance indicated by the distance data Energy characteristic parameters of echo signals generated by interference noise;
  • each echo signal is a noise echo signal.
  • each echo signal is a noise echo signal according to the energy characteristic parameter of each echo signal and the reference energy characteristic parameter, it is specifically used to:
  • the echo signal is a noise echo signal.
  • the processor 603 determines that the echo signal is a noise echo signal when the energy characteristic parameter of the echo signal is less than the reference energy characteristic parameter of the echo signal, Specifically used for:
  • the echo signal is a noise echo signal.
  • the reference distance data is determined according to the distance distribution between the interference noise generating the noise echo signal and the laser detection device.
  • the distance distribution follows a Poisson distribution or a Gaussian distribution.
  • one or more parameters in the distance distribution are determined according to the type of interference noise specified by the user.
  • the processor 603 determines that the echo signal is a noise echo signal when the energy characteristic parameter of the echo signal is less than the reference energy characteristic parameter of the echo signal, Specifically used for:
  • the energy characteristic parameter of the echo signal is less than the reference energy characteristic parameter of the echo signal, it is determined according to the distance data and the distance distribution between the interference noise generating the noise echo and the laser detection device The probability corresponding to the distance data;
  • the echo signal is a noise echo signal.
  • the distance distribution follows a Poisson distribution or a Gaussian distribution.
  • one or more parameters in the distance distribution are determined according to the type of interference noise specified by the user.
  • each echo signal is a noise echo signal according to the energy characteristic parameter of each echo signal and the reference energy characteristic parameter, it is specifically used to:
  • the echo signal is a valid echo signal.
  • the processor 603 determines the reference energy characteristic parameter of each echo signal according to the distance data of each echo signal, it is specifically used to:
  • the noise echo filtering curve is based on the reflectivity of the interference noise, multiple energy characteristic parameters of the interference noise, and multiple distance data corresponding to the multiple energy characteristic parameters of the interference noise Calibration.
  • the noise echo filtering curve is determined according to the type of interference noise specified by the user.
  • FIG. 7 is a schematic structural diagram of a movable platform provided by Embodiment 9 of the present invention. As shown in FIG. 7, the movable platform 700 includes:
  • a power system 702, installed on the fuselage 701, is used to provide power, wherein the power system includes one or more of a motor, an engine, a propeller, and an electric tune;
  • this embodiment also provides a computer-readable storage medium on which a computer program is stored, which is executed by a processor to implement the echo signal processing method described in the above embodiment.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are only schematic.
  • the division of the unit is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical, or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware, or in the form of hardware plus software functional units.
  • the above integrated unit implemented in the form of a software functional unit may be stored in a computer-readable storage medium.
  • the above software functional units are stored in a storage medium, and include several instructions to enable a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute the method described in each embodiment of the present invention Partial steps.
  • the foregoing storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code .

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Abstract

一种回波信号处理方法、设备及存储介质，该方法包括：发射光脉冲，并获取所述光脉冲对应的多个回波信号；确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据；根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。通过这种方式能够精准地确定当前采集到的多个回波信号中由干扰噪点产生的噪点回波信号，进而能够有效地提高激光探测设备探测目标的准确性，为可移动平台的安全移动提供了基础。

Description

回波信号处理方法、设备及存储介质 技术领域
本发明实施例涉及雷达领域，尤其涉及一种回波信号处理方法、设备及存储介质。
背景技术
现有技术中可移动平台，例如车辆、无人机、可移动机器人等搭载激光探测设备(例如激光雷达)，所述激光探测设备可以用于探测可移动平台周围的目标(例如障碍物)。
通常情况下，激光雷达所处的环境中存在干扰噪点，例如灰尘、雨、雾、霾、雪等物体。激光雷达对外发射一个光脉冲信号，光脉冲信号会遇到目标和干扰噪点，导致激光探测设备会接收到多个回波信号，其中，所述多个回波信号中包括由干扰噪点产生(即反射)的回波信号，即噪点回波信号。噪点回波信号会影响激光雷达对目标的准确检测。然而，现有技术中，在对激光探测设备接收到的噪点回波信号进行滤除时，很容易将目标产生的回波信号也一起滤除掉，导致激光雷达探测目标的准确性下降。
发明内容
本发明实施例提供一种回波信号处理方法、设备、系统及存储介质，以提高噪点回波信号识别的准确性，进而提高激光探测设备对目标检测的准确性。
本发明实施例的第一方面是提供一种回波信号处理方法，应用于激光探测设备，其特征在于，包括：
发射光脉冲，并获取所述光脉冲对应的多个回波信号；
确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据；
根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。
本发明实施例的第二方面是提供一种激光探测设备，所述设备包括：激光发射器、接收器和处理器；
所述激光器，用于发射光脉冲；
所述接收器，用于获取所述光脉冲对应的多个回波信号；
所述处理器，用于：
确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据；
根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。
本发明实施例的第三方面是提供一种可移动平台，包括：
机身；
动力系统，安装在所述机身，用于提供动力；
以及如第二方面所述的激光探测设备。
本发明实施例的第四方面是提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行以实现如第一方面所述的回波信号处理方法。
本实施例提供的回波信号处理方法、设备及存储介质，通过获取所述光脉冲对应的多个回波信号，确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据，根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。通过这种方式能够精准地确定当前采集到的多个回波信号中由干扰噪点产生的噪点回波信号，进而能够有效地提高激光探测设备探测目标的准确性，为可移动平台的安全移动提供了基础。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例提供的激光探测设备的结构图；
图2为本发明实施例提供的回波信号的处理方法的流程图；
图3为本发明实施例提供的不同反射率的物体产生的回波信号的回波能量与回波信号距离数据的关系的示意图；
图4为本发明实施例提供的雨雾和尘土回波信号的脉宽与回波信号距离数据的关系的示意图；
图5为本发明实施例提供的产生回波信号的干扰噪点与激光探测设备之间的距离分布图；
图6为本发明实施例提供的激光探测设备的结构图；
图7为本发明实施例提供的可移动平台的结构图；
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
需要说明的是，当组件被称为“固定于”另一个组件，它可以直接在另一个组件上或者也可以存在居中的组件。当一个组件被认为是“连接”另一个组件，它可以是直接连接到另一个组件或者可能同时存在居中组件。
除非另有定义，本文所使用的所有的技术和科学术语与属于本发明的技术领域的技术人员通常理解的含义相同。本文中在本发明的说明书中所使用的术语只是为了描述具体的实施例的目的，不是旨在于限制本发明。本文所使用的术语“及/或”包括一个或多个相关的所列项目的任意的和所有的组合。
下面结合附图，对本发明的一些实施方式作详细说明。在不冲突的情况下，下述的实施例及实施例中的特征可以相互组合。
图1为本发明实施例中提供的一种激光探测设备的结构示意图，为了进行示意性说明，以激光雷达为激光探测设备为例来进行示意性说明。如图1所示，该激光雷达可以包括激光器101、透镜102、控制器103、第一电机104、第二电机105、第一棱镜106、第二棱镜107、分束器108、接收器109和飞行时间(Time of Flight，TOF)模块110，其中，接收器109 包括光电二极管，例如，可以是雪崩光电二极管(Avalanche Photo Diode，APD)。以激光雷达探测与目标20之间的距离为例，激光雷达的激光器将电脉冲信号变成发散光脉冲信号，透镜将发散的光脉冲信号变成平行光脉冲信号发射出去，控制器(设置在芯片中)分别通过第一电机控制第一棱镜旋转，通过第二电机控制第二棱镜旋转，利用第一棱镜和第二棱镜的差速旋转，改变通过第一棱镜和第二棱镜后出射的光脉冲信号的方向，发射出去的光脉冲信号遇到目标之后，会反射回光脉冲信号，反射回来的光脉冲信号为回波信号，所述回波信号通过分束器进行分束并进入到接收器(包括APD)中，接收器将回波信号转换成电脉冲信号，并通过TOF(设置在芯片中)计算激光雷达与目标之间的距离，再根据激光雷达与目标之间的距离生成点云数据。
通常情况下，激光雷达所处的环境中存在干扰噪点，例如灰尘、雨雾、霾、雪等物体。激光雷达对外发射一个光脉冲信号，光脉冲信号会遇到目标和干扰噪点，导致激光探测设备会接收到多个回波信号，其中，所述多个回波信号中包括由干扰噪点产生(即反射)的回波信号，即噪点回波信号。噪点回波信号会影响激光雷达对目标的准确检测，需要将所述噪点回波信号滤除。
现有技术中是将多个回波信号中的第一个回波信号确定为有效回波信号或者将多个回波信号中能量最大的一个回波信号确定为有效回波，将其他的回波信号确定为噪点回波信号。然而，这种方式并不准确，极有可能将处于远处的目标产生的回波信号确定为噪点回波信号，即将远处的目标确定为干扰噪点。为了解决上述技术问题，本发明提供了一种回波信号处理方法、设备及存储介质。
图2为本发明实施例一提供的回波信号处理方法的流程示意图，所述噪点回波信号的处理方法应用于激光探测设备，如图2所示，所述方法包括：
步骤201、发射光脉冲信号，并获取所述光脉冲对应的多个回波信号；
具体地，如前所述，激光探测设备包括激光器和接收器。所述激光器可以发射光脉冲信号，所述光脉冲信号遇到目标和/或干扰噪点会产生反射产生多个回波信号，所述接收器可以接收该光脉冲对应的多个回波信号。
步骤202、确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据；
具体地，所述激光探测设备可以包括处理器，其中，所述处理器可以包括一个或者多个。所述处理器可以根据确定所述接收器接收到的多个回波信号中每一个回波信号对应的能量特征参数。其中，所述能量特征参数可以包括任何能够指示能量特征参数的信息，所述能量特征参数是根据所述回波信号的回波能量、脉宽、高度、面积中的至少一种确定的。进一步地，能量特征参数可以包括所述回波信号的回波能量、脉宽、高度、面积中的至少一种。另外，处理器还可以根据如前所述的TOF计算每一个回波信号对应的距离数据，其中，所述距离数据可以是激光探测设备与产生所述回波信号的物体之间的距离数据。
步骤203、根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。
具体地，每一个回波信号的能量特征参数和距离数据之后，并根据每一个回波信号的能量特征参数和距离数据确定该回波信号是否为干扰噪点产生的噪点回波信号，即根据每一个回波信号的能量特征参数和距离数据将多个回波信号中的噪点回波信号筛选出来。
本实施例提供的回波信号处理方法，通过获取所述光脉冲对应的多个回波信号，确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据，根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。通过这种方式能够精准地确定当前采集到的多个回波信号中由干扰噪点产生的噪点回波信号，进而能够有效地提高激光探测设备探测目标的准确性，为可移动平台的安全移动提供了基础。
在某些实施例中，所述根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为噪点回波信号包括：根据所述每一个回波信号的距离数据确定所述每一个回波信号的参考能量特征参数；根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号。
具体地，激光探测设备在获取到多个回波信号中每一个回波信号对应 的距离数据之后，可以根据所述每一个回波信号的距离数据确定每一个回波信号对应的参考能量特征参数，其中，所述参考能量特征参数可以用于指示干扰噪点在所述距离数据指示的距离处时由干扰噪点产生的回波信号的能量特征参数。在确定了每一个回波信号对应的能量特征参数之后，可以根据所述每一个回波信号的能量特征参数和参考能量特征参数确定回波能量特征参数和与其对应的参考能量参考信息之间的关系，根据所述关系确定所述每一个回波信号是否为噪点回波信号。
进一步地，所述根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号包括：当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号。
具体地，以回波信号的能量特征参数为回波信号的回波能量、参考能量特征性信息为参考回波能量为例来进行说明。激光雷达探测设备的接收器接收到的回波信号的回波能量主要由回波信号的距离数据和产生该回波信号的物体的反射率来确定，例如：
E intensity＝k*r/R 2  (1)
其中，E intensity为回波信号的回波能量，r为产生回波信号的物体的反射率，R为回波信号的距离数据，k为比例因子。
参见图3，不同的反射率的物体有如下回波能量与距离数据的关系曲线。从图3可知，回波能量与物体的反射率正相关，与距离数据指示的距离的平方负相关，在相同的距离时，物体的反射率越大，该物体产生的回波信号的回波能量越大。在通常情况下，干扰噪点的反射率与目标的反射率相比是很低的，例如，干扰噪点的反射率一般低于一个预设的反射率阈值，例如如图所示的3.2，反射率小于预设的反射率阈值的物体可以认为是干扰噪点，这里以预设的反射率阈值为3.2为例来进行说明。因此，可以认为当回波信号的距离数据和回波信号的回波能量构成的位置点在图3中的r＝3.2对应的曲线下方(图中阴影部分)时，可以认为该回波信号极有可能为干扰噪点产生的回波信号。进一步地，r＝3.2对应的曲线(可以称为噪点过滤曲线)上与每一个距离数据对应的回波能量即为该距离数据对应的参考回波能量，其中，所述参考回波能量可以用于指示干扰噪点在所述 距离数据指示的距离处时由干扰噪点产生的回波信号的回波能量。探测设备获取到每一个回波信号的距离数据和回波能量之后，可以根据所述每一个回波信号的距离数据确定与所述距离数据对应的参考回波能量，当所述回波信号的回波能量小于参考回波能量时，可以确定所述回波信号为干扰噪点产生的回波信号。
以回波信号的能量特征参数为回波信号的脉宽、参考能量特征参数为参考脉宽为例来进行说明。考虑到工程实际中计算的方面，可以对公式(1)进行转换得到如下公式(2)：
Figure PCTCN2019071018-appb-000001
其中，Pw为回波信号的脉宽，k为比例因子，r为反射率，R为雷达的探测距离，g -1为转换函数。
从公式(2)可以看出，回波信号的脉宽与物体的反射率正相关，与距离数据指示的距离的平方负相关，在相同的距离时，物体的反射率越大，该物体产生的回波信号的脉宽越大。如前所述，干扰噪点的反射率与目标的反射率相比是很低的，例如，干扰噪点的反射率一般低于一个预设的反射率阈值，例如所述预设的反射率阈值可以为雨雾或者尘土的反射率，反射率小于预设的反射率阈值的物体可以认为是干扰噪点。参见图4，图4示出了通过公式(2)确定的雨雾和尘土产生的回波信号的脉宽与对应的回波信号的距离数据的关系曲线(可以称为过滤曲线)，可以认为当回波信号的距离数据和回波信号的回波能量构成的位置点在图4中的雨雾的过滤曲线或者尘土的过滤曲线下方时，可以认为该回波信号极有可能为干扰噪点产生的回波信号。进一步地，雨雾的过滤曲线或者尘土的过滤曲线上与每一个距离数据对应的脉宽即为该距离数据对应的参考脉宽，其中，所述参考脉宽可以用于指示干扰噪点在所述距离数据指示的距离处时由干扰噪点产生的回波信号的脉宽。探测设备获取到每一个回波信号的距离数据和脉宽之后，可以根据所述每一个回波信号的距离数据确定与所述距离数据对应的参考脉宽，当所述回波信号的脉宽小于参考脉宽时，可以确定所述回波信号为干扰噪点产生的回波信号。
综上所述，激光探测设备在获取到回波信号的能量特征参数和参考能量特征参数之后，可以比较能量特征参数和参考能量特征参数之间的大小 关系，当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号。
进一步地，所述根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号包括：当回波信号的所述能量特征参数大于该回波信号的所述参考能量特征参数时，确定所述回波信号为有效回波信号，即确定所述回波信号为目标产生的回波信号。
在某些实施例中，所述根据所述每一个回波信号的距离数据确定所述每一个回波信号的参考能量特征参数包括：将所述回波信号的距离数据代入噪点回波过滤曲线中以确定所述回波信号的参考能量特征参数。
具体地，激光雷达探测设备在获取回波信号的距离数据之后，可以将所述距离数据代入到噪点回波过滤曲线中，其中，所述噪点回波过滤曲线用于指示干扰噪点的反射率、干扰噪点产生的所述多个回波信号的能量信息和与能量信息对应的距离数据之间的关系。例如，可以将回波信号的距离数据代入到如图3所示的r＝3.2对应的过滤曲线中、如图4所示的雨雾过滤曲线或者如图4所示的尘土过滤曲线中即可以确定出该回波信号的参考能量特征参数，进一步地，可以采用如前所述的方法根据回波信号的能量特征参数和参考能量特征参数确定所述回波信号是否为干扰噪点产生的噪点回波信号。
在某些实施例中，所述噪点回波过滤曲线是根据干扰噪点的反射率、干扰噪点产生的多个回波信号的能量特征参数、与所述多个回波信号的能量特征参数对应的多个距离数据标定得到的。
具体地，为了得到噪点过滤曲线，可以通过实验的方式方式获取干扰噪点产生的多个回波信号，获取所述多个回波信号的能量信息和与能量信息对应的距离数据。例如，继续参考图4，噪点过滤曲线可以为r＝r0时公式(2)对应的曲线，其中，r0为干扰噪点的反射率，进一步地，r0为雨雾或者尘土的反射率。在对噪点过滤曲线进行标定的过程中，可以获取干扰噪点产生的所述多个回波信号的脉宽和与脉宽对应的距离数据，其中，所述多个回波信号的脉宽和与脉宽对应的距离数据构成如图4所示多个位置点，根据干扰噪点的反射率、干扰噪点产生的多个回波信号的能量特征参数、与所述多个回波信号的能量特征参数对应的多个距离数据对公式(2) 进行多项式拟合即可以确定公式(2)中的g -1和k,即完成r＝r0时噪点过滤曲线的标定。
在某些实施例中，所述噪点回波过滤曲线是根据用户指定的干扰噪点的类型选中的。
具体地，噪点回波过滤曲线可以存储在激光雷达探测设备的存储设备中，在某些情况中，所述噪点回波过滤曲线可以包括多种。例如，如图4所示的尘土过滤曲线或者雨雾过滤曲线。用户可以根据激光探测设备所处的环境情况来选择对应的噪点过滤曲线。例如，当激光探测设备在雨雾环境中使用时，用户可以选中如图4所示的雨雾过滤曲线；当激光探测设备在灰层较多的环境中使用时，用户可以选中如图4所示的尘土过滤曲线。
在某些实施例中，所述噪点回波过滤曲线可以是所述激光探测设备根据识别到的环境类型选中的。
具体地，所述激光探测设备可以识别激光探测设备所处的环境类型，例如识别所述激光探测设备是处于雨雾环境还是处于尘土环境，并根据识别到的环境类型选中不同类型的噪点回波过滤曲线，例如，当识别所述激光探测设备是处于雨雾环境，选中如图4所示的雨雾过滤曲线，当识别所述激光探测设备是处于尘土环境，选中如图4所示的尘土过滤曲线。
在某些实施例中，所述当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号包括：当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述该回波信号的距离数据是否小于参考距离数据；若是，则确定所述回波信号为噪点回波信号。
具体地，当激光探测设备在确定回波信号的能量特征参数小于该回波信号的所述参考能量特征参数时，可以再进行进一步地判断。例如，考虑到干扰噪点一般为环境中微小的颗粒物体，激光探测设备接收到位于远处的干扰噪点产生的回波信号的概率是比较小的。因此，可以进一步地比较回波信号的距离数据与参考距离阈值进行比较，确定所述该回波信号的距离数据是否小于参考距离数据，若是，则确定所述回波信号为噪点回波信号，若否，则确定所述回波信号为有效回波信号。
进一步地，所述参考距离数据是根据产生噪点回波信号的干扰噪点与所述激 光探测设备之间的的距离分布确定的。
具体地，通过理论分析可知，产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离可能服从一个特定的距离分布，例如，所述距离分布为泊松分布或高斯分布。在这里以产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离分布为泊松分布为例，即产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离服从如下分布：
Figure PCTCN2019071018-appb-000002
根据不同类型的干扰噪点，所述λ取不同的值，例如，若所述干扰噪点为雨雾，可以选中所述所述λ为3.5，这样可以得到如图5所示的干扰噪点产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离分布图。观察所述距离分布图可知，所述干扰噪点主要分布在与激光探测设备相距10米的范围内。进一步地，可以根据所述距离分布确定参考距离阈值，例如所述参考距离阈值可以为10米，确定所述该回波信号的距离数据是否小于10米；若是，则确定所述回波信号为噪点回波信号。若否，可以确定所述回波信号为有效回波信号。
在某些情况中，所述距离分布的类型可以是根据用户指定的干扰噪点的类型确定的。
具体地，不同类型的干扰噪点产生的噪点回波信号的距离可能服从不同类型的距离分布，不同类型的距离分布可能使得所述参考距离数据不同。例如，雨雾产生的回波信号的距离数据可能服从泊松分布，尘土产生的回波信号的距离数据可能服从高斯分布。激光探测设备可以根据用户指定的干扰噪点的类型来确定与所述干扰噪点类型对应的类型的距离分布。
在某些情况中，所述距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。
具体地，不同类型的干扰噪点与所述激光探测设备之间的的距离分布中的参数可能会各不相同，不同参数可能使得所述参考距离数据不同，距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。例如，产生噪点回波信号的雨雾与所述激光探测设备之间的的距离分布和产生噪点回波信号的尘土与所述激光探测设备之间的的距离分布都为泊松分布，雨雾对应的泊松分布中的参数λ可以不同于尘土对应的泊松分布中的参数λ。激光探测设备可以根据用户指定的干扰噪点的类型来确定与所述干扰噪点类型对应的类型的距离分 布中一个或多个参数。例如激光探测设备可以根据用户选中的干扰噪点的类型确定泊松分布中的参数λ。
在某些实施例中，所述当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号包括：当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，根据所述距离数据和产生噪点回波的干扰噪点与所述激光探测设备之间的的距离分布确定该距离数据对应的概率；确定所述概率是否大于预设的概率阈值时，当是时，确定所述回波信号为噪点回波信号，当否时，确定所述回波信号为有效回波信号。
具体地，当激光探测设备在确定回波信号的能量特征参数小于该回波信号的所述参考能量特征参数时，可以再进行进一步地判断。考虑到干扰噪点一般为环境中微小的颗粒物体，激光探测设备接收到位于远处的干扰噪点产生的回波信号的概率是比较小的。因此，可以进一步地根据所述距离数据和产生噪点回波的干扰噪点与所述激光探测设备之间的的距离分布确定该距离数据对应的概率。如前所述，通过理论分析可知，产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离可能服从一个特定的距离分布，例如，所述距离分布服从泊松分布或高斯分布。
在这里以产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离分布服从泊松分布为例，即产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离服从如下分布：
Figure PCTCN2019071018-appb-000003
根据不同类型的干扰噪点，所述λ取不同的值，例如，若所述干扰噪点为雨雾，可以选中所述所述λ为3.5，这样可以得到如图5所示的干扰噪点产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离分布图。由图5可知，干扰噪点产生的回波信号的距离数据在0-10米的范围内时，其距离数据在泊松分布中的概率较大时，说明干扰噪点主要分布在1-10米范围内，干扰噪点产生的回波信号的距离数据10米之外的范围内时，其距离数据在泊松分布中的概率很小，说明干扰噪点不大可能分布在10米之外的范围。因此，激光探测设备可以根据所述距离数据和产生噪点回波的干扰噪点与所述激光探测设备之间的的距离分布(例如泊松分布)确定该距离数据对应的概率，其中，该距离数据对 应的概率可以包括该距离数据的一个距离区域对应的概率，所述距离区域的大小本领域技术人员可以根据需求选中。确定所述概率是否大于预设的概率阈值时(例如0.2或者0.25等等)，当是时，确定所述回波信号为噪点回波信号，当否时，确定所述回波信号为有效回波信号。
在某些实施例中，所述距离分布的类型可以是根据用户指定的干扰噪点的类型确定的。
具体地，不同类型的干扰噪点产生的噪点回波信号的距离可能服从不同类型的距离分布，不同类型的距离分布可能使得所述预设的概率阈值不同。例如，雨雾产生的回波信号的距离数据可能服从泊松分布，尘土产生的回波信号的距离数据可能服从高斯分布。激光探测设备可以根据用户指定的干扰噪点的类型来确定与所述干扰噪点类型对应的类型的距离分布。
在某些实施例中，所述距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。
具体地，不同类型的干扰噪点与所述激光探测设备之间的的距离分布中的参数可能会各不相同，不同参数可能使得所述预设的概率阈值不同，距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。例如，产生噪点回波信号的雨雾与所述激光探测设备之间的的距离分布和产生噪点回波信号的尘土与所述激光探测设备之间的的距离分布都服从泊松分布，雨雾对应的泊松分布中的参数λ可以不同于尘土对应的泊松分布中的参数λ。激光探测设备可以根据用户指定的干扰噪点的类型来确定与所述干扰噪点类型对应的类型的距离分布。激光探测设备可以根据用户选中的干扰噪点的类型确定泊松分布中的参数λ。
在某些实施例中，所述方法还包括：当确定所述回波信号为噪点回波信号时，滤除所述噪点回波信号。
图6为本发明实施例提供的激光探测设备的结构示意图，如图6所示，所述可移动平台600，包括：激光器601、接收器602和处理器603，其中，
所述激光器601，用于发射光脉冲；
所述接收器602，用于获取所述光脉冲对应的多个回波信号；
所述处理器603，用于：
确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据；
根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。
在某些实施例中，所述能量特征参数是根据所述回波信号的回波能量、脉宽、高度、面积中的至少一种确定的。
在某些实施例中，所述处理器603根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为噪点回波信号时，具体用于：
根据所述每一个回波信号的距离数据确定所述每一个回波信号的参考能量特征参数，其中，所述参考能量特征参数可以用于指示干扰噪点在所述距离数据指示的距离处时由干扰噪点产生的回波信号的能量特征参数；
根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号。
在某些实施例中，所述处理器603根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号时，具体用于：
当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号。
在某些实施例中，所述处理器603在当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号时，具体用于：
当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述该回波信号的距离数据是否小于参考距离数据；
若是，则确定所述回波信号为噪点回波信号。
在某些实施例中，所述参考距离数据是根据产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离分布确定的。
在某些实施例中，所述距离分布服从泊松分布或高斯分布。
在某些实施例中，所述距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。
在某些实施例中，所述处理器603在当回波信号的所述能量特征参数 小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号时，具体用于：
当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，根据所述距离数据和产生噪点回波的干扰噪点与所述激光探测设备之间的的距离分布确定该距离数据对应的概率；
当所述概率大于预设的概率阈值时，确定所述回波信号为噪点回波信号。
在某些实施例中，所述距离分布服从泊松分布或高斯分布。
在某些实施例中，所述距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。
在某些实施例中，所述处理器603根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号时，具体用于：
当回波信号的所述能量特征参数大于该回波信号的所述参考能量特征参数时，确定所述回波信号为有效回波信号。
在某些实施例中，所述处理器603根据所述每一个回波信号的距离数据确定所述每一个回波信号的参考能量特征参数时，具体用于：
将所述回波信号的距离数据代入噪点回波过滤曲线中以确定所述回波信号的参考能量特征参数，其中，所述噪点回波过滤曲线用于指示干扰噪点的反射率、干扰噪点产生的所述多个回波信号的能量信息和与能量信息对应的距离数据之间的关系。
在某些实施例中，所述噪点回波过滤曲线是根据干扰噪点的反射率、干扰噪点的多个能量特征参数、所述干扰噪点的与所述多个能量特征参数对应的多个距离数据标定得到的。
在某些实施例中，所述噪点回波过滤曲线是根据用户指定的干扰噪点的类型确定的。
图7为本发明实施例九提供的可移动平台的结构示意图，如图7所示，所述可移动平台700，包括：
机身701；
动力系统702，安装在所述机身701，用于提供动力，其中，所述动力系统包括电机、发动机、螺旋桨、电调中的一种或多种；
以及如上述任一实施例所述的激光探测设备703。
另外，本实施例还提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行以实现上述实施例所述的回波信号处理方法。
在本发明所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
上述以软件功能单元的形式实现的集成的单元，可以存储在一个计算机可读取存储介质中。上述软件功能单元存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本发明各个实施例所述方法的部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域技术人员可以清楚地了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功 能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。上述描述的装置的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (32)

  1. 一种噪点回波信号的处理方法，应用于激光探测设备，其特征在于，包括：
    发射光脉冲，并获取所述光脉冲对应的多个回波信号；
    确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据；
    根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。
  2. 根据权利要求1所述的方法，其特征在于，所述能量特征参数是根据所述回波信号的回波能量、脉宽、高度、面积中的至少一种确定的。
  3. 根据权利要求1或2所述的方法，其特征在于，
    所述根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为噪点回波信号包括：
    根据所述每一个回波信号的距离数据确定所述每一个回波信号的参考能量特征参数，其中，所述参考能量特征参数可以用于指示干扰噪点在所述距离数据指示的距离处时由干扰噪点产生的回波信号的能量特征参数；
    根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号。
  4. 根据权利要求3所述的方法，其特征在于，所述根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号包括：
    当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号。
  5. 根据权利要求4所述的方法，其特征在于，所述当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号包括：
    当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述该回波信号的距离数据是否小于参考距离数据；
    若是，则确定所述回波信号为噪点回波信号。
  6. 根据权利要求5所述的方法，其特征在于，所述参考距离数据是根据产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离分布确定的。
  7. 根据权利要求6所述的方法，其特征在于，所述距离分布包括泊松分布或高斯分布。
  8. 根据权利要求6或7所述的方法，其特征在于，所述距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。
  9. 根据权利要求4所述的方法，其特征在于，所述当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号包括：
    当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，根据所述距离数据和产生噪点回波的干扰噪点与所述激光探测设备之间的的距离分布确定该距离数据对应的概率；
    当所述概率大于预设的概率阈值时，确定所述回波信号为噪点回波信号。
  10. 根据权利要求9所述的方法，其特征在于，所述距离分布包括泊松分布或高斯分布。
  11. 根据权利要求10所述的方法，其特征在于，所述距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。
  12. 根据权利要求3-11任一项所述的方法，其特征在于，
    所述根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号包括：
    当回波信号的所述能量特征参数大于该回波信号的所述参考能量特征参数时，确定所述回波信号为有效回波信号。
  13. 根据权利要求3-12任一项所述的方法，其特征在于，所述根据所述每一个回波信号的距离数据确定所述每一个回波信号的参考能量特征参数包括：
    将所述回波信号的距离数据代入噪点回波过滤曲线中以确定所述回波信号的参考能量特征参数，其中，所述噪点回波过滤曲线用于指示干扰噪点的反射率、干扰噪点产生的所述多个回波信号的能量信息和与能量信息对应的距离数据之间的关系。
  14. 根据权利要求13所述的方法，其特征在于，其中，所述噪点回波过滤曲线是根据干扰噪点的反射率、干扰噪点的多个能量特征参数、所述干扰噪点的与所述多个能量特征参数对应的多个距离数据标定得到的。
  15. 根据权利要求13或14所述的方法，其特征在于，所述噪点回波过滤曲线是根据用户指定的干扰噪点的类型确定的。
  16. 一种激光探测设备，其特征在于，包括：激光器、接收器和处理器，其中，
    所述激光器，用于发射光脉冲；
    所述接收器，用于获取所述光脉冲对应的多个回波信号；
    所述处理器，用于：
    确定所述多个回波信号中每一个回波信号的能量特征参数和距离数据；
    根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为干扰噪点产生的噪点回波信号。
  17. 根据权利要求16所述的设备，其特征在于，所述能量特征参数是根据所述回波信号的回波能量、脉宽、高度、面积中的至少一种确定的。
  18. 根据权利要求16或17所述的设备，其特征在于，
    所述处理器根据每一个回波信号的能量特征参数和距离数据确定所述每一个回波信号是否为噪点回波信号时，具体用于：
    根据所述每一个回波信号的距离数据确定所述每一个回波信号的参考能量特征参数，其中，所述参考能量特征参数可以用于指示干扰噪点在所述距离数据指示的距离处时由干扰噪点产生的回波信号的能量特征参数；
    根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号。
  19. 根据权利要求18所述的设备，其特征在于，所述处理器根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号时，具体用于：
    当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号。
  20. 根据权利要求19所述的设备，其特征在于，所述处理器在当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号时，具体用于：
    当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述该回波信号的距离数据是否小于参考距离数据；
    若是，则确定所述回波信号为噪点回波信号。
  21. 根据权利要求20所述的设备，其特征在于，所述参考距离数据是根据产生噪点回波信号的干扰噪点与所述激光探测设备之间的的距离分布确定的。
  22. 根据权利要求21所述的设备，其特征在于，所述距离分布包括 泊松分布或高斯分布。
  23. 根据权利要求21或22所述的设备，其特征在于，所述距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。
  24. 根据权利要求19所述的设备，其特征在于，所述处理器在当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，确定所述回波信号为噪点回波信号时，具体用于：
    当回波信号的所述能量特征参数小于该回波信号的所述参考能量特征参数时，根据所述距离数据和产生噪点回波的干扰噪点与所述激光探测设备之间的的距离分布确定该距离数据对应的概率；
    当所述概率大于预设的概率阈值时，确定所述回波信号为噪点回波信号。
  25. 根据权利要求24所述的设备，其特征在于，所述距离分布包括泊松分布或高斯分布。
  26. 根据权利要求25所述的设备，其特征在于，所述距离分布中的一个或多个参数是根据用户指定的干扰噪点的类型确定的。
  27. 根据权利要求18-26任一项所述的设备，其特征在于，
    所述处理器根据所述每一个回波信号的能量特征参数和参考能量特征参数确定所述每一个回波信号是否为噪点回波信号时，具体用于：
    当回波信号的所述能量特征参数大于该回波信号的所述参考能量特征参数时，确定所述回波信号为有效回波信号。
  28. 根据权利要求18-27任一项所述的设备，其特征在于，所述处理器根据所述每一个回波信号的距离数据确定所述每一个回波信号的参考能量特征参数时，具体用于：
    将所述回波信号的距离数据代入噪点回波过滤曲线中以确定所述回 波信号的参考能量特征参数，其中，所述噪点回波过滤曲线用于指示干扰噪点的反射率、干扰噪点产生的所述多个回波信号的能量信息和与能量信息对应的距离数据之间的关系。
  29. 根据权利要求28所述的设备，其特征在于，其中，所述噪点回波过滤曲线是根据干扰噪点的反射率、干扰噪点的多个能量特征参数、所述干扰噪点的与所述多个能量特征参数对应的多个距离数据标定得到的。
  30. 根据权利要求28或29所述的设备，其特征在于，所述噪点回波过滤曲线是根据用户指定的干扰噪点的类型确定的。
  31. 一种可移动平台，包括：
    机身；
    动力系统，安装在所述机身，用于提供动力；
    以及如权利要求16-30任一项所述的激光探测设备。
  32. 一种计算机可读存储介质，其特征在于，其上存储有计算机程序，所述计算机程序被处理器执行以实现如权利要求1-15任一项所述的方法。
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