The present disclosure relates to a technical area of unmanned aerial vehicle, and in particular to a target signal detection method and device, and an unmanned aerial vehicle and an agricultural unmanned aerial vehicle regarding the same.
Unmanned aerial vehicles have been employed in a variety of areas, such as aerial photo-imaging, agricultural plant protection, electric power inspection, and disaster relief.
Unmanned aerial vehicles are often equipped with detection devices, such as radar detection devices, time-of-flight (TOF) detection devices, and visual sensors. The unmanned aerial vehicle detects, via the detection device, distance, position, and velocity of a nearby target object relative to the unmanned aerial vehicle.
When conducting detection of a target object, the detection device of the unmanned aerial vehicle may receive noise or interfering signals reflected from the ground surface or the crops on the ground, where the noise reflection signals may interfere with an accurate detection of the target object by the detection device.
In accordance with the present disclosure, there is provided a method of detecting target signals including obtaining detection signals from a detection device, the detection device being to detect a target object around an unmanned aerial vehicle, selecting a test signal and neighboring signals from the detection signals, determining a signal threshold corresponding to the test signal according to the neighboring signals, and determining whether the test signal includes a target signal from the target object according to the signal threshold.
Also in accordance with the present disclosure, there is provided an unmanned aerial vehicle including a vehicle body, a power system supported on the vehicle body to provide flight power, a detection device supported on the vehicle body to detect a target object, a flight controller in connection with the power system to providing flight control, and a target signal detection device including a processor configured to perform a method of detecting target signal, where the method includes obtaining detection signals from a detection device, the detection device being to detect a target object around an unmanned aerial vehicle, selecting a test signal and neighboring signals from the detection signals, determining a signal threshold corresponding to the test signal according to the neighboring signals, and determining whether the test signal includes a target signal from the target object according to the signal threshold.
Also in accordance with the present disclosure, there is provided a method of detecting target signals including obtaining a test signal and neighboring signals from a detection device in communication with an unmanned aerial vehicle, where the detection device detects a target object around the unmanned aerial vehicle, and where the neighboring signals include a first number of neighboring signals and a second number of neighboring signals, sending one of the first number of neighboring signals to a sliding window detector at a first timepoint, sending one of the second number of neighboring signals to the sliding window detector at a second timepoint, sending the test signal into the sliding window detector at a third timepoint, where the first timepoint is earlier in time than the third timepoint and the second timepoint is later in time than the third timepoint, determining a signal threshold according to the first and second numbers of the neighboring signals, and determining that the test signal is a valid signal when the test signal is greater than the signal threshold.
Objectives, features, and advantages of the embodiments are more readily understandable in reference to the accompanying drawings described below. In the accompanying drawings, the embodiments are described without limiting the scope of the present disclosure.
The present disclosure is described in view of the embodiments but the embodiments as described do not necessarily limit the scope of any of the claims. To those skilled in the technical art, many suitable changes and improvements may be made to the embodiments. Such suitable changes and improvements are understood to be included in the scope defined by the claims
As illustratively depicted in
By way of example, the detection device may be a radar detection device. The radar detection device may be a microwave radar sensor. The microwave radar sensor emits electromagnetic waves. When the target object 12 around the unmanned aerial vehicle 10 receives the electromagnetic waves, the target object reflects the electromagnetic waves to form target signals and particularly target reflection signals. According to the electromagnetic waves emitted by the microwave sensor and the target reflection wave from the target object 12, distance, position of the target object 12 relative to the unmanned aerial vehicle 10 is determined.
The unmanned aerial vehicle 10 may be an agricultural unmanned aerial vehicle. When the agricultural unmanned aerial vehicle conducts operations, the waves emitted by the radar detection device are likely received at the crops and the ground surface, such that many reflection signals received at the radar detection device include detectable noise signals. These noise waves may interfere with detection of the target object 12. To solve this problem, a signal threshold is introduced in the process of detecting target signals reflected from the target object. As illustratively depicted in
There may be certain probability of error associated with method illustratively depicted in
The present disclosure provides a target signal detection method.
At step S401, multiple detection signals are obtained by a detection device, where the detection device is employed to detect target objects near or around an unmanned aerial vehicle.
The method involves an executive body which may be a processor 13 of the unmanned aerial vehicle 10 as illustratively depicted in
In certain embodiments, the target signal detection method may be executed by a ground station device 51 as illustratively depicted in
The unmanned aerial vehicle 10 includes a communication system 52, where the unmanned aerial vehicle 10 sends the detection signals from the detection device 11 down to the ground station device 51 via the communication system 52, and where the ground station device 51 detects reflection signals as reflected out from the target objects. The unmanned aerial vehicle 10 communicates with the ground station device 51 via wired or wireless communications. As illustratively depicted in
At step S402, a test signal and neighboring signals which are neighbors to the test signal are selected from the detection signals, a signal threshold is corresponding to the test signal is determined according to signal values of the first neighboring signals.
The detection signals detected by the detection device 11 include reflection signals which may be time domain analog signals. The processor 13 may convert the analog signals to digital signals and obtains sampled signals from the digital signals. For example, v(t1), v(t2) . . . and v(tm), represent sampled signals in a number of m, each of which being a test signal. As illustratively depicted in
As illustratively depicted in
As illustratively depicted in
As illustratively depicted in
Therefore, a new signal or datapoint enters the sliding window every time the slide window moves one unit forward along direction 71 with the arrow shown. As illustratively depicted in
As illustratively depicted in
As illustratively depicted in
As illustratively depicted in
In some embodiments, and according to the test signals neighboring the to-be-detected test signal, the signal threshold particular to the to-be-detected test signal is determined. In particular, estimated strength value of the interfering signals included in the predetermined number of neighboring test signals is determined according to the predetermined number of neighboring test signals neighboring the to-be-detected test signal; thereafter, the signal threshold particular or corresponding to the to-be-detected test signal is determined according to the factor T and also according to the estimated strength value of the interfering signals included in the predetermined number of neighboring test signals.
As illustratively depicted in
According to the predetermined number of neighboring test signals neighboring the to-be-detected test signal, the step of determining average strength value of noise signal included in the predetermined number of neighboring test signals may include: according to the first predetermined number of neighboring test signals positioned ahead of a test signal further ahead of the to-be-detected test signal, and according to the second predetermined number of neighboring test signals positioned behind of a test signal further behind the to-be-detected signal, an average strength value of the noise signal is determined according to the first and second predetermined numbers of test signals.
As illustratively depicted in
As illustratively depicted in
One exemplary relationship works like this: the estimate value Z on the interfering signal is determined according to an average of signal strength values corresponding the predetermined number of neighboring test signals, such as number 2n of test signals, where the factor T is related to a false-alarm rate.
The estimated strength value of the interfering signals present in 2n test samples corresponding to the reference units x1, x2, . . . , xn and reference units y1, y2, . . . and yn may be determined according to an average of amplitudes of the 2n test samples, and may be represented by the equation (1) shown below.
As illustratively depicted in
Alternatively, the estimated strength value of the interfering signals present in the predetermined number of neighboring test signals may be determined by a sum strength value of the predetermined number of neighboring test signals. The factor T is related to both the false-alarm rate and the predetermined number.
In particular, the estimated strength value of the interfering signals present in 2n test signals corresponding to the reference units x1, x2, . . . , xn and reference units y1, y2, . . . and yn may be determined according to the sum of amplitudes of the 2n test signals, and may be represented by the equation (2) shown below.
where the factor T may be represented by the equation (3) shown below.
T=P
FA
−1/R−1 (3)
where PFA represents the false-alarm rate.
At step S403, and according to the signal threshold corresponding to the test signal, it is determined as to whether the test signal includes the target reflection signal from the target object.
As illustratively depicted in
In some embodiments, and according to the signal threshold corresponding to the to-be-detected signal, the step of determining if the to-be-detected signal includes the target reflection signal includes: when the signal strength of the to-be-detected is greater than the signal threshold, the to-be-detected test signal is determined to include the target reflection signal; when the signal strength of the to-be-detected is smaller than the signal threshold, the to-be-detected test signal is determined to not include the target reflection signal.
In particular, and when D is greater than threshold S, the to-be-detected test signal is determined to include target reflection signal; and when D is smaller or equal to threshold S, the to-be-detected test signal is determined to not include the target reflection signal, or the to-be-detected test signal includes only interference and noise signals, where a relationship between D and S may be represented by equation (4) shown below.
D>T·Z, H
1
D≤T·Z, H
0 (4)
In particular, when D is greater than T·Z , H1 is established, where H1 represents that the to-be-detected test signal includes the target reflection signal; and D is smaller than or equal to T·Z , H0 is established, where H0 represents that the to-be-detected test signal includes only the interfering and noise signals.
In some embodiments, the method further includes deleting those test signals whose signal strength or amplitude is smaller than or equal to their corresponding signal threshold. In particular, and as illustratively depicted in
According to embodiment(s) of the present disclosure, multiple detection signals are obtained at the detection device, each of the detection signals is set as the to-be-detected test signal, which is the test signal whose amplitude is placed inside of the detection unit D of the sliding window described herein elsewhere, and according to detection signal near or neighboring the to-be-detected signal, the signal threshold particular and corresponding to the to-be-detected signal is determined. Accordingly, each of the test signals is provided with its own particular signal threshold, instead of a general signal threshold not otherwise particular to any specific test signal. According to its particular and corresponding signal threshold, each of the test signals is better positioned for a determination as to whether the test signal includes the target reflection signal. Accordingly, false alarm is also avoided where a noise signal with signal strength greater than the otherwise general signal threshold does not indeed include the target reflection signal and yet erroneously regarded as a signal including the target reflection signal. Accordingly, detection accuracy of the target object can be increased, and false-alarm rate may be decreased.
The present disclosure provides a target signal detection method.
At step S1001, detection signals are obtained from a detection device, the detection device being employed to detect a target object near or around an unmanned aerial vehicle.
Step S1001 is similar to step S401.
At step S1002, a flight height or flight altitude is obtained from the unmanned aerial vehicle.
As illustratively depicted in
The processor 13 obtains from the detection device 11 the flight altitude of the unmanned aerial vehicle, or the flight height of the unmanned aerial vehicle relative to the ground surface.
At step S1003, and according to the flight altitude of the unmanned aerial vehicle, a false-alarm rate is adjusted or modified.
The processor 13 adjusts the false-alarm rate according to the flight altitude of the unmanned aerial vehicle 10 relative to the ground surface. As described herein elsewhere, the signal threshold corresponding to the test signal is S=T·Z , where factor T is related to the false-alarm rate PFA. As the false-alarm rate PFA changes, the factor T changes also, and therefore the signal threshold S=T·Z changes accordingly. The false-alarm rate and the signal threshold S=T·Z may be adaptively adjusted according to the flight altitude of the unmanned aerial vehicle.
The step of adjusting the false-alarm rate according to the flight height of the unmanned aerial vehicle may include: when the flight altitude of the unmanned aerial vehicle is greater than a preset altitude, increasing the false-alarm rate; and when the flight altitude of the unmanned aerial vehicle is smaller than the preset altitude, decreasing the false-alarm rate.
In other words, and when the flight altitude of the unmanned aerial vehicle is greater than the preset altitude, the false-alarm rate PFA increases, and the signal threshold S decreases. When the unmanned aerial vehicle such as the agricultural unmanned aerial vehicle is in flight, it becomes less likely for the noise reflection signals from the crops or the ground surface to be captured by the detection device of the unmanned aerial vehicle; therefore, by decreasing the signal threshold S, the likelihood of small objects such as wires in the sky from being overlooked is decreased, and accordingly to reduce missing-alarm rate.
When the flight altitude of the unmanned aerial vehicle is smaller than the preset altitude, the false-alarm rate PFA decreases, and the signal threshold S increases. When the unmanned aerial vehicle such as the agricultural unmanned aerial vehicle is of a relatively low flight altitude, it becomes more likely for the noise reflection signals from the crops or the ground surface to be captured by the detection device of the unmanned aerial vehicle; therefore, by increasing the signal threshold S, the likelihood of the crops and the ground surface from being considered as target objects is decreased, and accordingly to reduce false-alarm rate.
At step S1004, each of multiple detection signals is set as the to-be-detected test signal, the signal threshold of the to-be-detected test signal is determined according to the test signals near or neighboring the to-be-detected test signal and the adjusted or modified false-alarm rate.
The signal threshold particular to the to-be-detected test signal may be expressed as S=T·Z , where factor T is related to the false-alarm rate. When the false-alarm rate PFA changes, factor T changes also, and therefore the threshold S=T·Z changes accordingly too. Z is related to X+Y, where X+Y is determined according to the test signals near or neighboring the to-be-detected test signal. The signal threshold S particular to the to-be-detected test signal can be determined according to the test signals near or neighboring the to-be-detected test signal and according to the adjusted or modified false-alarm rate PFA.
At step S1005, and according to the signal threshold particular to the to-be-detected test signal, it is determined as to whether the to-be-detected test signal includes the target reflected signal.
Step S1005 may be carried out similarly as step S403 both in theory and operation.
When the unmanned aerial vehicle is of a flight altitude greater than the preset altitude, increasing false-alarm rate such that the signal threshold is decreased, which in turn works to reduce the likelihood of small interfering objects such as wires in the sky from being overlooked, and accordingly missing alarm rate is decreased. When the unmanned aerial vehicle is of a flight altitude smaller than the preset altitude, decreasing false-alarm rate such that the signal threshold is increased, which in turn works to reduce the likelihood of crops and other ground surface objects from being regarded as target objects, and accordingly false alarm rate is decreased. Accordingly, missing alarm rate and false alarm rate may be effectively reduced in the process of obstacle avoidance radar detection conducted by the unmanned aerial vehicle, to then reduce impact of noise signals, and to then elevate detection performance on the target objects.
The present disclosure provides a target signal detection device.
In some embodiments, the detection device includes at least one of a radar detection device, a TOF detection device, an ultrasonic detection device, and a visual detection device.
In some embodiments, the processor 112 determines the signal threshold of the to-be-detected test signal according to the test signals near or neighboring the to-be-detected test signal. Estimated strength value of the interfering signals within the predetermined number of neighboring test signals is determined according to the predetermined number of neighboring test signals near or neighboring the to-be-detected test signal. According to the estimated strength value of the interfering signals within the predetermined number of neighboring test signals, and according to the factor T, the signal threshold corresponding to the to-be-detected test signal is determined.
In some embodiments, the processor 112 determines an estimated strength value of interfering signals present in the predetermined number of neighboring test signals according to the predetermined number of neighboring test signals that neighbor or are near the to-be-detected test signal. According to the first predetermined number of neighboring test signals positioned ahead of a test signal further ahead of the to-be-detected test signal, and according to the second predetermined number of neighboring test signals positioned behind of a test signal further behind the to-be-detected signal, an average strength value of the noise signal is determined according to the first and second predetermined numbers of test signals.
In some embodiments, the estimated value of the strength of the interfering signals is determined according to average strength value of the predetermined number of neighboring test signals.
In some embodiments, the estimated value of the strength of the interfering signals is determined according to the sum strength value of the predetermined number of neighboring test signals. In some embodiments, the factor T is related to the false-alarm rate and the predetermined number.
In some embodiments, the processor 112 determines if the to-be-detected signal includes the target reflection signal from the target object according to the signal threshold of the to-be-detected signal. In particular, when the signal strength of the to-be-detected test signal is determined to be greater than the signal threshold, the to-be-detected signal is determined to include the target reflection signal of the target object; and when the signal strength of the to-be-detected test signal is determined to be smaller than or equal to the signal threshold, the to-be-detected signal is determined to not include the target reflection signal of the target object.
In some embodiments, the processor 112 is further employed to delete or cancel signals as detected by the detection device whose signal strength is smaller than or equal to the signal threshold.
The target detection device mentioned in this embodiment is similar to the target detection device as illustratively depicted in
According to embodiment(s) of the present disclosure, multiple detection signals are obtained at the detection device, each of the detection signals is set as the to-be-detected test signal, which is the test signal whose amplitude is placed inside of the detection unit D of the sliding window described herein elsewhere, and according to detection signal near or neighboring the to-be-detected signal, the signal threshold particular and corresponding to the to-be-detected signal is determined. Accordingly, each of the test signals is provided with its own particular signal threshold, instead of a general signal threshold not otherwise particular to any specific test signal. According to its particular and corresponding signal threshold, each of the test signals is better positioned for a determination as to whether the test signal includes the target reflection signal. Accordingly, also false alarm is avoided where a noise signal with signal strength greater than the otherwise general signal threshold does not indeed include the target reflection signal and yet erroneously regarded as a signal including the target reflection signal. Accordingly, detection accuracy of the target object can be increased, and false-alarm rate may be decreased.
The present disclosure provides a target signal detection device. As illustratively depicted in
In some embodiments, the processor 112 adjusts false alarm rate according to the flight altitude of the unmanned aerial vehicle. In particular, when the flight altitude of the unmanned aerial vehicle is greater than the preset altitude, the false-alarm rate is increased; and when the flight altitude of the unmanned aerial vehicle is smaller than the preset altitude, the false-alarm rate is decreased.
The processor 112 determines the signal threshold corresponding or particular to the to-be-detected test signal according to test signals near or neighboring the to-be-detected test signal. In particular, the signal threshold corresponding to the to-be-detected test signal is determined according to the test signals neighboring the to-be-detected test signal and the modified or adjusted false-alarm rate.
The target signal detection device described here may be similar to the device as illustratively depicted in
When the unmanned aerial vehicle is of a flight altitude greater than the preset altitude, increasing false-alarm rate such that the signal threshold is decreased, which in turn works to reduce the likelihood of small interfering objects such as wires in the sky from being overlooked, and accordingly missing alarm rate is decreased. When the unmanned aerial vehicle is of a flight altitude smaller than the preset altitude, decreasing false-alarm rate such that the signal threshold is increased, which in turn works to reduce the likelihood of crops and other ground surface objects from being regarded as target objects, and accordingly false alarm rate is decreased. Accordingly, missing alarm rate and false alarm rate may be effectively reduced in the process of obstacle avoidance radar detection conducted by the unmanned aerial vehicle, to then reduce impact of noise signals, and to then elevate detection performance on the target objects.
The present disclosure includes an unmanned aerial vehicle.
The target signal detection device 1210 may be similar to the target signal detection device 110 both in theory and operation.
According to embodiment(s) of the present disclosure, multiple detection signals are obtained at the detection device, each of the detection signals is set as the to-be-detected test signal, which is the test signal whose amplitude is placed inside of the detection unit D of the sliding window described herein elsewhere, and according to detection signal near or neighboring the to-be-detected signal, the signal threshold particular and corresponding to the to-be-detected signal is determined. Accordingly, each of the test signals is provided with its own particular signal threshold, instead of a general signal threshold not otherwise particular to any specific test signal. According to its particular and corresponding signal threshold, each of the test signals is better positioned for a determination as to whether the test signal includes the target reflection signal. Accordingly, also false alarm is avoided where a noise signal with signal strength greater than the otherwise general signal threshold does not indeed include the target reflection signal and yet erroneously regarded as a signal including the target reflection signal. Accordingly, detection accuracy of the target object can be increased, and false-alarm rate may be decreased.
The present disclosure also provides an agricultural unmanned aerial vehicle.
The detection device 1301 rotates about its rotation shaft and may, for example, conducts continuous rotations. The rotation shaft of the detection device 1301 may be perpendicular to the yaw axis of the agricultural unmanned aerial vehicle, and parallel to the pitch axis of the agricultural aerial vehicle.
In some embodiments, the detection device 1301 is connected to a tripod of the agricultural unmanned aerial vehicle.
According to embodiment(s) of the present disclosure, multiple detection signals are obtained at the detection device, each of the detection signals is set as the to-be-detected test signal, which is the test signal whose amplitude is placed inside of the detection unit D of the sliding window described herein elsewhere, and according to detection signal near or neighboring the to-be-detected signal, the signal threshold particular and corresponding to the to-be-detected signal is determined. Accordingly, each of the test signals is provided with its own particular signal threshold, instead of a general signal threshold not otherwise particular to any specific test signal. According to its particular and corresponding signal threshold, each of the test signals is better positioned for a determination as to whether the test signal includes the target reflection signal. Accordingly, false alarm is also avoided where a noise signal with signal strength greater than the otherwise general signal threshold does not indeed include the target reflection signal and yet erroneously regarded as a signal including the target reflection signal. Accordingly, detection accuracy of the target object can be increased and false-alarm rate may be decreased.
Devices, systems, programs, and methods in actions, orders, steps, and periods, as referenced to in the present disclosure, the claims, and the drawings, may be in any suitable order. In particular, terms such as “first” and “next” may be used to simplify the task of description, but not to imply that such order is necessary.
Several functional units of the embodiments of the present disclosure may be integrated into a processing unit, or may each exist as an independent entity. Each of such units may be presented as a hardware unit or a combination or integration of a hardware and a software.
The software function units may be stored in a computer readable storage medium. The storage medium includes instructions when executed cause to the processor to perform one or more of the steps described herein. Such storage medium may include a U-disk, a mobile hard disk, a read-only memory (ROM), a random-access memory (RAM), and any other suitable storage disks and discs.
The present disclosure is described in view of the embodiments but the embodiments as described do not necessarily limit the scope of any of the claims. Certain embodiments or features of the embodiments described herein may be combined; however, not all such combinations are necessarily required for the solutions to the disclosure. To those skilled in the technical art, many suitable changes and improvements may be made to the embodiments. Such suitable changes and improvements are understood to be included in the scope defined by the claims.
This application is a continuation of International Application No. PCT/CN2017/116888, filed Dec. 18, 2017, the entire content of which is incorporated herein by reference.
Number | Date | Country | |
---|---|---|---|
Parent | PCT/CN2017/116888 | Dec 2017 | US |
Child | 16713716 | US |