CN112346062B - Ultrasonic distance measurement method in long-distance scene - Google Patents

Ultrasonic distance measurement method in long-distance scene Download PDF

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CN112346062B
CN112346062B CN202011312555.1A CN202011312555A CN112346062B CN 112346062 B CN112346062 B CN 112346062B CN 202011312555 A CN202011312555 A CN 202011312555A CN 112346062 B CN112346062 B CN 112346062B
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CN112346062A (en
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邱棚
朱雅鸿
张新钰
梁政
杨柳旭
杨德睿
郭世纯
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Beijing Otereb Technology Co ltd
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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
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/02—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems using reflection of acoustic waves
    • G01S15/06—Systems determining the position data of a target
    • G01S15/08—Systems for measuring distance only
    • G01S15/10—Systems for measuring distance only using transmission of interrupted, pulse-modulated waves
    • 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
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/539—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section

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  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
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Abstract

The invention discloses an ultrasonic distance measurement method in a long-distance scene, which comprises the following steps: generating a measuring signal according to a measuring rule of compressed sensing, and transmitting the measuring signal through an ultrasonic transducer at a transmitting end; the receiving end samples and filters the received signal, and then effective signal interception is carried out on the filtered sampled signal; recovering sparse channel signals from the intercepted effective signals by using a compressed sensing recovery algorithm; obtaining a first path signal and a first path arrival time from the sparse channel signal by using peak value screening; and multiplying the arrival time of the first path by the propagation speed to obtain the distance from the transmitting end to the receiving end. The method can measure accurate multipath channels, realize high-precision ranging, and simultaneously ensure the stability of measurement; the signal can be obtained at a lower sampling frequency, super resolution of ranging is realized, and ranging cost is reduced.

Description

Ultrasonic distance measurement method in long-distance scene
Technical Field
The invention relates to the field of ultrasonic positioning, in particular to an ultrasonic distance measurement method in a long-distance scene.
Background
In the long-distance ranging of mechanical waves or electromagnetic waves, the problem of multipath is difficult to avoid; the multipath signals can cause the ranging accuracy to be greatly reduced, and particularly, the influence on the ranging stability is obvious; increasing bandwidth is an effective means of suppressing the multipath problem.
But the bandwidth of the ultrasonic transducer is limited, and the multipath problem is particularly prominent; the use of ultrasonic waves in long-range distance measurement scenes is limited; in addition, the high ultrasonic frequency requires a high sampling rate, which results in high acquisition cost and large data processing amount, and further increases the use cost.
The undersampling characteristic of compressed sensing can greatly reduce the sampling frequency and the use cost. Meanwhile, the multi-path signals contained in the aliasing signals can be accurately distinguished, so that the influence of the multi-path on the accuracy and stability of the distance measurement is avoided.
Disclosure of Invention
The invention aims to overcome the technical defects and provides a low-cost ultrasonic distance measuring method in a long-distance scene.
In order to achieve the above object, the present invention provides an ultrasonic ranging method in a long-distance scene, wherein the method comprises:
generating a measuring signal according to a measuring rule of compressed sensing, and transmitting the measuring signal through an ultrasonic transducer at a transmitting end;
the receiving end samples and filters the received signal, and then effective signal interception is carried out on the filtered sampled signal;
recovering sparse channel signals from the intercepted effective signals by using a compressed sensing recovery algorithm;
obtaining a first path signal and a first path arrival time from the sparse channel signal by using peak value screening;
and multiplying the arrival time of the first path by the propagation speed to obtain the distance from the transmitting end to the receiving end.
As an improvement of the above method, the measuring signal is generated according to the measuring rule of compressed sensing and transmitted by an ultrasonic transducer at the transmitting end; the method specifically comprises the following steps:
designing a measurement signal x according to a measurement criterion of compressed sensing; x is a set of sequences that obey a gaussian distribution, uniform distribution, bernoulli distribution, or chi-square distribution;
transmitting signal y of ultrasonic transducersExpressed as:
ys＝h*x
wherein h is the impulse response sequence of the ultrasonic transducer.
As an improvement of the above method, the receiving end samples and filters the received signal, and then performs effective signal interception on the filtered sampled signal; the method specifically comprises the following steps:
sampling the received signal at a rate related to the channel signal length, the number of samples being at least 1/3 times the signal length;
filtering the sampled signal by using a band-pass filter; the band-pass filter is an FIR filter or an IIR filter;
and carrying out effective signal interception on the filtered sampling signal to obtain a processed sampling signal.
As an improvement of the above method, the method for performing effective signal interception on the filtered sampling signal comprises: a threshold method, an energy method or a crossing method;
threshold value method: setting the position exceeding the value 1/3 as the starting time of the signal according to the maximum value of the received signal at the maximum propagation distance, and intercepting M data from the time to the back;
energy method: taking the square sum of adjacent k signals as the energy of the signal segment; 1/3, setting the threshold value as the maximum energy of the signal at the maximum propagation distance; intercepting M data from the position exceeding the threshold value for the first time;
a traversing method: setting a threshold value, and counting the times of the signal crossing the threshold value in a period of time as a judgment basis; setting crossing times according to the central frequency and time of the signal; when the value is reached for the first time, M data are intercepted backwards.
As an improvement of the above method, the sparse channel signal is recovered from the intercepted effective signal by using a compressed sensing recovery algorithm; the method specifically comprises the following steps:
generating a measurement matrix U consisting of the transmission signalsm×n：
Figure BDA0002790264560000021
Wherein a measurement vector usIs at ysRespectively compensating n 0 before and after;
Figure BDA0002790264560000031
m represents the length of the intercepted effective signal; n represents the length of the channel signal to be recovered; y issIs determined by the impulse response sequence h and the measurement signal x;
matrix Um×nIs Toeplitz matrix, and then the processed sampling signal
Figure BDA0002790264560000032
Writing is in matrix form:
Figure BDA0002790264560000033
recovering sparse channel signal d from processed sampling signal by using compressed sensing recovery algorithmn。
As an improvement of the above method, the recovery algorithm is: a greedy matching pursuit algorithm, a convex relaxation algorithm, a bayesian-like algorithm, or a neural network algorithm.
As an improvement of the above method, the first path signal and the arrival time thereof are obtained from the sparse channel signal by using peak value screening; the method specifically comprises the following steps:
after channel recovery, a group of sparse channel signals d is obtainedn(ii) a A location with a signal represents a signal arriving at that time; selecting one third of the peak value as a threshold value, wherein the first peak value exceeding the threshold value is a first path signal;
acquiring a first path arrival time from the first path signal; the time is a value obtained by adding the initial time of the intercepted signal and the time corresponding to the position of the first path signal in the intercepted signal.
The invention has the advantages that:
1. the method can measure accurate multipath channels, realize high-precision distance measurement in an ultra-long distance scene, and simultaneously ensure the stability of measurement;
2. the method of the invention can acquire signals with lower sampling frequency, realize super resolution of distance measurement and reduce system cost.
Drawings
FIG. 1 is a schematic illustration of a linear measurement;
FIG. 2 is a schematic diagram of the ultrasonic ranging method in a long-distance scene according to the present invention;
FIG. 3 is a schematic diagram of a generated measurement signal;
FIG. 4 is a schematic diagram of an impulse response sequence;
FIG. 5 is a schematic diagram of multiple propagation paths of a signal from a transmitting end to a receiving end;
FIG. 6 is a representation of a signal before filtering;
fig. 7 is a representation of the filtered signal.
Detailed Description
The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.
The technical principle of the invention is as follows: considering that the signal's arrival path from the transmitter to the receiver is limited, the multipath channel can be represented as a set of sparse signals with respect to time; the accuracy and efficiency of compressed sensing in detecting sparse signals are far higher than those of the traditional method; designing a transmitting signal form according to the theoretical requirement of compressed sensing, generating a corresponding measurement matrix, and realizing efficient measurement of a multipath channel; the first peak of the multipath channel represents the position where the first path signal arrives, i.e., the time of flight of the signal.
Compressed sensing technology: compressed sensing is an efficient acquisition for sparse signals; breaking through the traditional Nyquist sampling law, and directly measuring the information content of the signal; the required measurement quantity is related to the signal quantity of the signal, namely sparsity; the compressed sensing is divided into three parts:
1) criteria for measurement
Finite isometric Property:
Figure BDA0002790264560000041
2) linear measurement
Figure BDA0002790264560000042
As shown in fig. 1.
3) Recovery algorithm
Sparsity constraints are added in the solution so that the algorithm can recover high-dimensional signals from low-dimensional measurements.
As shown in fig. 2, the present invention provides an ultrasonic ranging method in a long-distance scene, where the method includes:
step 1) generating a measurement signal
Designing a measuring signal according to a measuring rule of compressed sensing; a group of sequences which are randomly distributed and obey Gaussian distribution, uniform distribution, Bernoulli distribution, chi-square distribution and the like; a sequence composed of a row randomly selected from encoding matrixes such as a Hadamard (Hadamard) matrix, an Optical Orthogonal code (Optical Orthogonal Codes) matrix, a discrete Chirp encoding matrix and the like; as shown in fig. 3.
Step 2) signal transmission-ultrasonic transducer
The bandwidth of the transducer is limited, and signals cannot be transmitted without loss; the transfer characteristics of the transducer need to be considered; characterized by the impulse response sequence (h) of the transducer, as shown in fig. 4; after passing through the transducer, the transmit signal can be expressed as:
ys＝h*x
step 3) channel transmission-multipath channel
The propagation path of the signal from the transmitting end to the receiving end is not unique, as shown in fig. 5; the received signal is generated by superposition of the transmitted signals with different delays and attenuations:
Figure BDA0002790264560000051
the above equation can be rewritten as a convolution of the channel signal and the transmit signal:
Figure BDA0002790264560000052
the vector d in the above equation can represent the characteristics of the multipath channel, and the signal is sparse.
Step 4) Signal reception-AD sampling
According to the nyquist sampling theorem, the sampling rate needs to be guaranteed to be at least 2 times greater than the signal frequency; in practical engineering application, the frequency of the signal is often required to be more than 10 times that of the signal; the compressed sensing can break through the Nyquist limit, the sampling rate is related to the length of a channel signal, and the sampling number only needs to reach 1/3;
step 5) Signal Filtering-band pass Filter
Selecting a pass band characteristic based on the transmit transducer characteristic; noise interference in the circuit acquisition process is eliminated; FIR and IIR filters can be selected; the signals before and after filtering are shown in fig. 6 and 7.
Step 6) effective signal interception
Threshold value method: setting the position exceeding the value 1/3 as the starting time of the signal according to the maximum value of the received signal at the maximum propagation distance, and intercepting M data from the time to the back;
energy method: and taking the square sum of adjacent k signals as the energy of the signal segment. The threshold value is set to 1/3 based on the maximum energy of the signal at the maximum propagation distance. Intercepting M data from the position exceeding the threshold value for the first time;
a traversing method: setting a threshold value, and counting the times of the signal crossing the threshold value in a period of time as a judgment basis. Setting the crossing times according to the central frequency and time of the signal (n-Tf)c). When the numerical value is reached for the first time, M data are intercepted backwards;
step 7) generating a measurement matrix
The measurement matrix is formed by the signals emitted by the transducers:
Figure BDA0002790264560000053
wherein a measurement vector usIs at ysRespectively compensating n 0 before and after;
Figure BDA0002790264560000061
m represents the length of the intercepted effective signal; n represents the length of the channel signal to be recovered; y issIs determined by the impulse response sequence h and the measurement signal x;
in general, n-length channel signals are recovered using data of m sampling points. One sample point represents one measurement of the signal of length bit n, and m sample points represent m measurements of the signal. Compressed sensing theory indicates that the number of samples m can be much smaller than the signal length n.
Matrix Um×nIs Toeplitz matrix, and then the processed sampling signal
Figure BDA0002790264560000062
Writing is in matrix form:
Figure BDA0002790264560000063
recovering sparse channel signal d from processed sampling signal by using compressed sensing recovery algorithmn。
Step 8) channel recovery-compressed sensing recovery algorithm
Recovering a channel signal d from the sampling signal; the problem is underdetermined, the solution space is infinite; the ability to employ compressed sensing to restore the signal is required; common recovery algorithms can be used: greedy matching pursuit methods (MP, OMP, CoSaMp), convex relaxation methods (BP, IPM, GPSR), bayesian methods (BCS, MCS), and neural network methods.
Step 9) Peak screening
Obtaining a group of sparse signals after channel recovery; a location with a signal represents a signal arriving at that time; considering that the signal strength is higher than that of a direct signal due to the fact that a plurality of signals arrive at the same time in certain positions, the maximum value cannot be selected as a first signal path; one third of the peak value is selected as a threshold value, the first peak value exceeding the threshold value is the first path signal,
step 10) distance solution
The time of the position of the first path is obtained after the peak value is screened, and the initial time of the interception signal is added to obtain the arrival time of the first path; the distance from the transmitting end to the receiving end can be obtained by multiplying the time by the propagation speed.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (5)

1. A method of ultrasonic ranging in a long-range scene, the method comprising:
generating a measuring signal according to a measuring rule of compressed sensing, and transmitting the measuring signal through an ultrasonic transducer at a transmitting end; the method specifically comprises the following steps:
designing a measurement signal x according to a measurement criterion of compressed sensing; x is a set of sequences that obey a gaussian distribution, uniform distribution, bernoulli distribution, or chi-square distribution;
transmitting signal y of ultrasonic transducersExpressed as:
ys＝h*x
wherein h is an impulse response sequence of the ultrasonic transducer;
the receiving end samples and filters the received signal, and then effective signal interception is carried out on the filtered sampled signal;
recovering sparse channel signals from the intercepted effective signals by using a compressed sensing recovery algorithm; the method specifically comprises the following steps:
generating a measurement matrix U consisting of the transmission signalsm×n：
Figure FDA0003071123170000011
Wherein a measurement vector usIs at ysRespectively compensating n 0 before and after;
Figure FDA0003071123170000012
m represents the length of the intercepted effective signal; n represents the length of the channel signal to be recovered; y issIs determined by the impulse response sequence h and the measurement signal x;
matrix Um×nIs Toeplitz matrix, and then the processed sampling signal
Figure FDA0003071123170000013
Writing is in matrix form:
Figure FDA0003071123170000014
recovering sparse channel signal d from processed sampling signal by using compressed sensing recovery algorithmn；
Obtaining a first path signal and a first path arrival time from the sparse channel signal by using peak value screening;
and multiplying the arrival time of the first path by the propagation speed to obtain the distance from the transmitting end to the receiving end.
2. The ultrasonic ranging method in the long-distance scene according to claim 1, wherein the receiving end samples and filters the received signal, and then performs effective signal interception on the filtered sampled signal; the method specifically comprises the following steps:
sampling the received signal at a rate related to the channel signal length, the number of samples being at least 1/3 times the signal length;
filtering the sampled signal by using a band-pass filter; the band-pass filter is an FIR filter or an IIR filter;
and carrying out effective signal interception on the filtered sampling signal to obtain a processed sampling signal.
3. The ultrasonic ranging method in the long-distance scene according to claim 2, wherein the method for performing effective signal interception on the filtered sampling signal comprises: a threshold method, an energy method or a crossing method;
threshold value method: according to the maximum value of the received signal in the maximum propagation distance, setting the 1/3 position exceeding the maximum value as the starting time of the signal, and intercepting M data from the time to the back;
energy method: taking the square sum of adjacent k signals as the energy of the signal segment; 1/3, setting a threshold as the maximum energy of the signal according to the maximum energy of the signal at the maximum propagation distance; intercepting M data from the position exceeding the threshold value for the first time;
a traversing method: setting a threshold value, and counting the times of the signal crossing the threshold value in a period of time as a judgment basis; setting crossing times according to the central frequency and time of the signal; when the crossing times are reached for the first time, M data are intercepted backwards.
4. The ultrasonic ranging method in a distant scene according to claim 1, wherein the recovery algorithm is: a greedy matching pursuit algorithm, a convex relaxation algorithm, a bayesian-like algorithm, or a neural network algorithm.
5. The ultrasonic ranging method in the long-distance scene according to claim 4, wherein the first path signal and the arrival time thereof are obtained from the sparse channel signal by using peak value screening; the method specifically comprises the following steps:
after channel recovery, a group of sparse channel signals d is obtainedn(ii) a A location with a signal represents the arrival of a signal at the corresponding time; selecting one third of the peak value as a threshold value, wherein the first peak value exceeding the threshold value is a first path signal;
acquiring a first path arrival time from the first path signal; the time is a value obtained by adding the initial time of the intercepted signal and the time corresponding to the position of the first path signal in the intercepted signal.
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