CN115184898A

CN115184898A - Beat signal analysis method, beat signal analysis device, electronic device, and computer-readable storage medium

Info

Publication number: CN115184898A
Application number: CN202210795727.8A
Authority: CN
Inventors: 张弛; 李鲲
Original assignee: Shenzhen North Wake Technology Co ltd
Current assignee: Shenzhen North Wake Technology Co ltd
Priority date: 2022-07-06
Filing date: 2022-07-06
Publication date: 2022-10-14

Abstract

The embodiment of the invention provides a beat frequency signal analysis method, a beat frequency signal analysis device, electronic equipment and a computer readable storage medium, and relates to the technical field of laser radars, wherein the beat frequency signal analysis method comprises the following steps: and performing multi-channel time delay and multiplexing processing on the signals to be processed to obtain a plurality of beat frequency signals with time delay difference and cascade connection of each channel. Windowing is carried out on the beat frequency signals of each channel, FFT operation is carried out on each beat frequency signal subjected to windowing, and a plurality of FFT operation result data streams are obtained. And analyzing to obtain a channel result corresponding to the beat signal of each channel based on each FFT operation result data stream, and processing each channel result according to the time delay sequence relation to obtain the time frequency data of the signal to be processed, thereby realizing the reliable and comprehensive analysis of the beat signal.

Description

Beat signal analysis method, beat signal analysis device, electronic device, and computer-readable storage medium

Technical Field

The invention relates to the technical field of laser radars, in particular to a beat frequency signal analysis method and device, electronic equipment and a computer readable storage medium.

Background

Frequency Modulated Continuous Wave (FMCW) lidar is a lidar in which the optical carrier Frequency continuously and periodically changes and continuously emits light, and by means of coherent detection, target reflected light and laser emitted light are coherent to generate a beat signal, and the characteristics of the beat signal represent a modulation Frequency difference introduced by target distance delay and a doppler Frequency difference introduced by relative speed. The distance and speed information of the target can be demodulated by measuring the beat frequency signal. Through research, signal spectrum analysis is mainly performed on beat frequency signals by adopting Fast Fourier Transform (FFT) at present, and an analysis result is relatively limited and cannot meet application requirements.

Disclosure of Invention

One of the objects of the present invention includes, for example, providing a beat signal analysis method, apparatus, electronic device and computer-readable storage medium to at least partially improve the comprehensiveness of the beat signal analysis result to meet application requirements.

Embodiments of the invention may be implemented as follows:

in a first aspect, an embodiment of the present invention provides a beat signal analysis method, including:

carrying out multichannel delay and multiplexing processing on the signals to be processed to obtain a plurality of beat frequency signals of which each channel has delay difference and is cascaded;

windowing the beat frequency signal of each channel;

performing FFT operation on each beat frequency signal subjected to windowing processing to obtain a plurality of FFT operation result data streams; each FFT operation result data stream comprises a frequency domain amplitude real part signal and an imaginary part signal of each beat frequency signal after windowing processing, and a corresponding frequency index value in time sequence;

analyzing to obtain a channel result corresponding to the beat signal of each channel based on each FFT operation result data stream;

and processing the channel results according to a time delay sequence relation to obtain time-frequency data of the signal to be processed.

In an alternative embodiment, the method further comprises the step of obtaining the signal to be processed, which comprises:

obtaining a beat frequency signal generated by coherent beat frequency of a transmission light signal and a reflection light signal of the FMCW laser radar; the transmitted light signal is a frequency modulation continuous wave laser signal transmitted by the FMCW laser radar, and the reflected light signal is a light signal which is received by the FMCW laser radar and is reflected after the frequency modulation continuous wave laser reaches a set target;

and performing analog-to-digital conversion on the beat frequency signal to obtain an intermediate frequency digital signal serving as a signal to be processed.

In an optional embodiment, the step of performing multi-channel delay and multiplexing on the signal to be processed to obtain multiple beat signals with delay difference and cascade connection of each channel includes:

inputting the signals to be processed into an FPGA, and outputting a plurality of beat signals with stepped time sequence delay difference and parallel channels based on a plurality of parallel double-port Block RAMs in the FPGA;

the two ports of the dual-port Block RAM are provided with different operation addresses, and the output of the two ports has a specified delay difference based on the different operation addresses.

In an optional embodiment, the step of windowing the beat signal of each channel includes:

generating a data sequence of a Hamming window;

adjusting the data bit width of the data sequence to be a designated bit width, and then taking the data bit width as an initialization file of a ROM in the FPGA;

circularly reading the ROM in the FPGA, and taking output data of the ROM as a Hamming window data stream;

and multiplying the Hamming window data streams with the beat signals of the channels to obtain the windowed beat signals of each channel.

In an optional embodiment, the step of performing an FFT operation on each of the windowed beat signals to obtain a plurality of FFT operation result data streams includes:

aiming at the beat frequency signal of each channel after windowing, respectively calculating the square of a real part signal and the square of an imaginary part signal of the frequency domain amplitude of the beat frequency signal based on the multiplier added to the corresponding channel in the FPGA;

adding the squares of the real part signal and the imaginary part signal to obtain a module value square value of the frequency domain amplitude of the beat frequency signal of each channel after windowing;

the step of analyzing and obtaining a channel result corresponding to the beat signal of each channel based on each FFT operation result data stream includes:

performing peak value detection on each module value square value to obtain a frequency domain amplitude maximum value and a frequency index maximum value corresponding to each channel;

the step of processing the results of each channel according to the time-delay sequence relationship to obtain the time-frequency data of the signal to be processed includes:

and carrying out serial conversion on the frequency domain amplitude maximum value and the frequency index maximum value corresponding to each channel according to a time delay sequence relation to obtain a one-dimensional frequency index value sequence.

In an optional implementation manner, a counter for incrementing cycles and a state machine with the same number of states as the number of channels are arranged in the FPGA, wherein each state of the state machine corresponds to each channel arranged in time sequence;

the step of performing serial conversion on the frequency domain amplitude maximum value and the frequency index maximum value corresponding to each channel according to a time delay sequence relationship to obtain a one-dimensional frequency index value sequence includes:

under the condition that the counter is the maximum value, state transition is carried out based on the state machine, the maximum frequency index value corresponding to the channel corresponding to the state is taken, and a one-dimensional serial frequency index value sequence is obtained;

calculating to obtain beat frequency according to the FFT point number and the operation clock frequency;

and converting the one-dimensional serial frequency index value sequence into a time-frequency curve based on the beat frequency.

In an alternative embodiment, in the case where the set target is in a stationary state, the method further includes calculating a distance between the FMCW lidar and the set target according to the following formula:

d＝cTf _iF /(4BW)

wherein f is _iF The stable frequency in the time frequency data is obtained; BW is the bandwidth range of the tone of the transmitted optical signal; t is the frequency modulation period of the emitted light signal; c is the speed of light;

in the case that the set target is in a moving state, the method further comprises calculating the moving speed of the set target according to the following formula:

fd＝2vf/c

wherein fd is the Doppler frequency obtained by analyzing the time-frequency data; v is the moving speed of the set target; f is laser carrier frequency; and c is the speed of light.

In a second aspect, an embodiment of the present invention provides a beat signal analysis apparatus, including:

the signal processing module is used for carrying out multichannel delay and multiplexing processing on the signals to be processed to obtain a plurality of beat frequency signals with delay difference and cascade connection of each channel, and windowing processing is carried out on the beat frequency signals of each channel;

the signal analysis module is used for carrying out FFT operation on each beat frequency signal subjected to windowing processing to obtain a plurality of FFT operation result data streams; analyzing to obtain a channel result corresponding to the beat signal of each channel based on each FFT operation result data stream; processing the channel results according to a time delay sequence relation to obtain time-frequency data of the signal to be processed;

each FFT operation result data stream comprises a frequency domain amplitude real part signal and an imaginary part signal of each beat frequency signal after windowing processing, and a corresponding frequency index value in time sequence.

In a third aspect, the present invention provides an electronic device comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the beat signal analysis method according to any of the preceding embodiments when executing the program.

In a fourth aspect, the present invention provides a computer-readable storage medium, which includes a computer program, and the computer program controls an electronic device where the computer-readable storage medium is located to execute the beat signal analysis method according to any one of the foregoing embodiments.

The beneficial effects of the embodiment of the invention include, for example: through the ingenious processing flow, the time-frequency data of the beat frequency signals are analyzed, the comprehensiveness of beat frequency signal analysis results is improved, various application requirements are met, and data support can be provided for distance measurement, speed measurement and the like.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 shows a schematic diagram of an application scenario provided in an embodiment of the present invention.

Fig. 2 is a schematic flow chart illustrating a beat signal analysis method according to an embodiment of the present invention.

Fig. 3 is another schematic flow chart of a beat signal analysis method according to an embodiment of the present invention.

Fig. 4 shows a logic block diagram of multi-channel delay multiplexing according to an embodiment of the present invention.

Fig. 5 is a logic block diagram illustrating a multiplication of a beat signal and a window function according to an embodiment of the present invention.

Fig. 6 shows a logic block diagram of an FFT frequency measurement of a multi-channel beat signal according to an embodiment of the present invention.

Fig. 7 shows a logic block diagram of a frequency domain amplitude modulo calculation according to an embodiment of the present invention.

Fig. 8 shows a logic block diagram of peak search after modulus of parallel FFT frequency domain amplitude according to an embodiment of the present invention.

Fig. 9 is a logic diagram for performing serial conversion according to the timing relationship between channels according to an embodiment of the present invention.

Fig. 10 is a schematic flow chart illustrating a beat signal analysis method according to an embodiment of the present invention.

FIG. 11 illustrates a coherent beat frequency model of the reflected light from a relatively stationary object provided by embodiments of the present invention.

FIG. 12 illustrates a coherent beat frequency model of the reflected light from a moving object in accordance with an embodiment of the present invention.

Fig. 13 is a block diagram illustrating an exemplary structure of a beat signal analysis apparatus according to an embodiment of the present invention.

An icon: 100-an electronic device; 110-a memory; 120-a processor; 130-a communication module; 140-beat signal analysis means; 141-a signal processing module; 142-signal analysis module.

Detailed Description

Compared with a Time of flight (TOF) laser radar, the laser radar based on the FMCW technology (FMCW laser radar for short) has the advantages of being strong in anti-interference performance, high in detection sensitivity, capable of measuring speed in real Time and the like, and can promote the development of a new generation of unmanned technology. Therefore, real-time and accurate measurement and analysis of the beat frequency signal have great significance for improving the performance of the FMCW laser radar.

The beat frequency signal measurement and analysis method mainly adopted at present is Fast Fourier Transform (FFT), the direct FFT method frequency spectrum measurement is a signal frequency spectrum analysis method widely adopted, the signal frequency spectrum can be effectively measured in a large number of application scenes, and the basic principle is to intercept a section of signal for Fast Fourier transform to obtain all frequency components in the intercepted signal.

Research shows that the direct FFT method can only obtain frequency domain information of the intercepted signal on the whole, and cannot obtain time information of each frequency component in the signal. The frequency domain information of the beat frequency signal generated by receiving light and emitting light of the FMCW laser radar is changed along with time, and the change trend has an important effect on analyzing the beat frequency signal, namely, the time domain information and the frequency domain information of the beat frequency signal are both taken into consideration when the beat frequency signal is measured and analyzed, so that the direct FFT method has certain limitation when the beat frequency signal is analyzed, cannot meet the application requirements, and cannot provide reliable support for functions of FMCW laser radar such as ranging and speed measurement.

Therefore, aiming at the FMCW laser radar beat frequency signal, how to ensure that the time domain characteristics are recorded while the frequency domain characteristics of the beat frequency signal are measured and analyzed provides reliable parameter support for realizing the functions of FMCW laser radar ranging, speed measurement and the like, and is a problem to be solved.

Based on the above research, embodiments of the present invention provide a scheme for analyzing a beat signal, where the beat signal is subjected to multi-channel delay multiplexing, and each channel is processed separately to analyze and obtain time-frequency information, such as a time-frequency curve, of the beat signal, so as to provide reliable parameter support for implementing functions of FMCW lidar ranging, speed measurement, and the like.

The defects existing in the above solutions are the results obtained after the inventor has practiced and studied carefully, and therefore, the discovery process of the above problems and the solutions proposed by the embodiments of the present invention below for the above problems should be the contributions of the inventor in the invention process.

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.

It is to be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.

Referring to fig. 1, a block diagram of an electronic device 100 provided in this embodiment is shown, where the electronic device 100 in this embodiment may be a server, a processing device, a processing platform, and the like capable of performing data interaction and processing. For example, the FPGA may be independent of the FPGA, may be the FPGA itself, or may be integrated with the FPGA. The electronic device 100 includes a memory 110, a processor 120, and a communication module 130. The memory 110, the processor 120 and the communication module 130 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines.

The memory 110 is used to store programs or data. The Memory 110 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.

The processor 120 is used to read/write data or programs stored in the memory 110 and perform corresponding functions.

The communication module 130 is configured to establish a communication connection between the electronic device 100 and another communication terminal through the network, and to transmit and receive data through the network.

It should be understood that the structure shown in fig. 1 is only a schematic structural diagram of the electronic device 100, and the electronic device 100 may also include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.

Referring to fig. 2, a flowchart of a beat signal analysis method according to an embodiment of the present invention may be executed by the electronic device 100 shown in fig. 1, for example, may be executed by the processor 120 in the electronic device 100. The beat signal analysis method includes S110 to S150.

And S110, performing multi-channel time delay and multiplexing processing on the signals to be processed to obtain a plurality of beat frequency signals with time delay difference and cascade connection of each channel.

And S120, windowing the beat frequency signal of each channel.

And S130, performing FFT operation on each beat frequency signal subjected to windowing processing to obtain a plurality of FFT operation result data streams.

And S140, analyzing and obtaining a channel result corresponding to the beat signal of each channel based on each FFT operation result data stream.

And S150, processing the channel results according to a time delay sequence relation to obtain time frequency data of the signals to be processed.

In the embodiment of the invention, the time-frequency data of the signal to be processed is obtained by analyzing the signal to be processed through multi-channel delay, multiplexing, windowing and FFT (fast Fourier transform algorithm) operation, so that the comprehensiveness of the beat frequency signal analysis result is improved, and various application requirements can be met, for example, data support can be provided for distance measurement, speed measurement and the like.

In S110, the signal to be processed may be obtained in various ways, and as long as multi-channel delay and multiplexing processing are performed, multiple beat signals with delay difference and cascade connection of each channel may be obtained.

Illustratively, the signal to be processed may be obtained by: a beat frequency signal generated by coherent beat frequency of the transmission light signal and the reflection light signal of the FMCW laser radar is obtained. The transmitting light signal is a frequency modulation continuous wave laser signal transmitted by the FMCW laser radar, and the reflecting light signal is a light signal which is received by the FMCW laser radar and is reflected after the frequency modulation continuous wave laser reaches a set target. And performing analog-to-digital conversion on the beat frequency signal to obtain an intermediate frequency digital signal serving as a signal to be processed.

The signal to be processed can also be obtained by: the reflected light signal can be received by other photoelectric detection devices, such as a Silicon photomultiplier (Silicon photomultiplier), to generate a beat signal, and the beat signal is analog-to-digital converted to obtain an intermediate frequency digital signal as a signal to be processed.

Referring to fig. 3, the FMCW lidar may include an FMCW laser and a photodetector, and the FMCW lidar emits continuous frequency-modulated laser based on the FMCW laser, and generates target reflected light when the emitted light reaches a target (a set target), and the target reflected light and the emitted light generate beat signals through the photodetector. The beat signal is converted into an intermediate frequency (time domain) digital signal after analog-to-digital conversion (ADC), so as to obtain a signal to be processed in S110.

In S110, the plurality of beat signals may be obtained by performing multi-channel delay parallel multiplexing on the signals to be processed. For example, the signal to be processed may be input to an FPGA, and based on a multi-channel parallel dual-port Block RAM in the FPGA, a plurality of beat signals with a stepped timing delay difference for each channel and parallel for each channel may be output. The two ports of the dual-port Block RAM are provided with different operation addresses, and the output of the two ports has a specified delay difference based on the different operation addresses.

Illustratively, continuing to refer to fig. 3, the intermediate frequency digital signal is input to the FPGA, and the FPGA performs multi-channel delay parallel multiplexing on the intermediate frequency digital signal, so as to obtain a plurality of beat signals.

In an implementation manner, please refer to fig. 4 in combination, the number of channels may be n _ channels, and the delay module may be implemented by a dual-port Block RAM in the FPGA chip. The two port outputs with the specified delay difference n _ delay can be realized by setting different operation addresses of the two ports. One path of beat frequency signal is accessed into a plurality of paths of parallel RAMs, and each path of RAM is set with n _ delay as delay output and cascaded, thus obtaining the multichannel parallel beat frequency signal with step time sequence delay difference of each channel.

The number n _ channel of the channels multiplexed in parallel and the number n _ delay of the delayed clock cycles can be flexibly configured according to requirements.

In one implementation, the multi-channel parallel signals with step delay differences may be implemented by an FPGA off-chip RAM chip, or by designing a FIFO inside the FPGA.

With continued reference to fig. 3, after obtaining the multi-channel time-delay multiplexed beat signal based on S110, a windowing operation is performed on each channel beat signal. Optionally, to prevent spectral leakage, cosine windows may be added for each channel.

Exemplarily, in S120, windowing the beat signal of each channel may be implemented by: generating a data sequence of a Hamming window, adjusting the data bit width of the data sequence to be a designated bit width, taking the adjusted data bit width as an initialization file of a ROM in the FPGA, circularly reading the ROM in the FPGA, taking output data of the ROM as a Hamming window data stream, and multiplying the Hamming window data stream by the beat signals of each channel to obtain the beat signals of each channel after windowing.

In an implementation manner, please refer to fig. 5 in combination, a group of Hamming window data sequences may be generated by Matlab, where the sequence length is N, the data bit width of the data sequence is adjusted to be a designated bit width, and then the data bit width is used as an initialization file (data) of an ROM in an FPGA chip, and the ROM is read in a loop in the FPGA, and the data output by the ROM is a Hamming window data stream with a certain data bit width. Multiplying the Hamming window data stream by the beat signal of each channel in the above S110, so as to obtain a windowed n _ channel multi-channel beat signal. The length N of the data sequence of the Hamming window can be flexibly configured according to requirements.

In one implementation, the windowing mode may be implemented by storing an external RAM chip of the FPGA, an external ROM chip of the FPGA, or an internal instantiated ROM of the FPGA.

In S130, obtaining the FFT operation result data stream may be implemented as follows: and respectively calculating the square of a real part signal and the square of an imaginary part signal of the frequency domain amplitude of the beat frequency signal on the basis of the multiplier added to the corresponding channel in the FPGA aiming at the beat frequency signal of each channel after windowing. And adding the squares of the real part signal and the imaginary part signal to obtain a module value square value of the frequency domain amplitude of the beat frequency signal of each channel after windowing.

Accordingly, the channel result in S140 may be achieved by: and carrying out peak value detection on each module value square value to obtain a frequency domain amplitude maximum value and a frequency index maximum value corresponding to each channel. The time-frequency data in S150 may be implemented as follows: and carrying out serial conversion on the frequency domain amplitude maximum value and the frequency index maximum value corresponding to each channel according to a time delay sequence relation to obtain a one-dimensional frequency index value sequence.

In one implementation, referring to fig. 3 and fig. 6 in combination, the FFT operation result data stream in S130 can be obtained by performing FFT frequency measurement on each channel of the multi-channel beat signal after windowing in S120 in each N-point window period. For example, an FFT operation core is added for each channel, the FFT operation core is accessed after the multiplication of the beat signal of each channel by the window function, the number of FFT operation points is N, which is the same as the above-mentioned number of windowed points, thereby performing FFT operation on the beat signal in each window. Thus, each channel outputs a set of FFT operation result data stream containing the frequency domain amplitude real part signal data _ real and imaginary part signal data _ imag of the data in each window, and a corresponding frequency index value index in time series. Wherein, the frequency index value index is a data stream which is sequentially increased and circulated from 0 to N-1.

Referring to fig. 3 and 7 in combination, after the FFT frequency measurement is implemented, modulus calculation is performed on the amplitude of the frequency measurement result of each channel, the real part and the imaginary part of the frequency domain amplitude of each channel form a complex signal of the frequency domain amplitude, two multipliers are added to each channel in the FPGA to calculate the squares of the real part signal and the imaginary part signal, and the squares of the real part signal and the imaginary part signal are added to obtain a square value amp _ square of the modulus of the frequency domain amplitude of each channel. Since the modulus of the frequency domain amplitude is a positive number, the variation trend of the modulus is the same as the variation trend of the modulus square, and therefore the subsequent processing can be directly carried out by using the modulus square, and the frequency domain amplitude modulus square value amp _ suqare and the corresponding frequency index value index of the n _ channel multichannel are obtained.

Referring to fig. 8, the frequency domain amplitude square value amp _ suqare of each channel is detected, and the frequency domain amplitude maximum value amp _ max and the frequency index value index _ max of the corresponding maximum value in each window of each channel of n _ channel are obtained by detecting the peak value with the frequency index value index ∈ [0, n/2-1] corresponding to the frequency domain amplitude square value.

In the FPGA, a counter for increasing cycles and a state machine having the same number of states as the number of channels are provided, where each state of the state machine corresponds to each channel arranged in time sequence, in S150, the frequency domain amplitude maximum value and the frequency index maximum value corresponding to each channel are serially converted according to a time delay sequence relationship to obtain a one-dimensional frequency index value sequence, which can be implemented by the following steps: and under the condition that the counter is the maximum value, performing state transition based on the state machine, and taking the maximum frequency index value corresponding to the channel corresponding to the state to obtain a one-dimensional serial frequency index value sequence. And calculating to obtain the beat frequency according to the FFT point number and the operation clock frequency. And converting the one-dimensional serial frequency index value sequence into a time-frequency curve based on the beat frequency.

In an implementation manner, please refer to fig. 9 in combination, the channel results in S140 are serially converted according to the inter-channel delay time sequence relationship, so as to obtain a one-dimensional frequency index value sequence, which is a time-frequency curve of the beat signal. And designing a state machine state _ machine in the FPGA, wherein the number of the states of the state machine is the same as the number of parallel channels and is n _ channel. And each state corresponds to each channel which is arranged in sequence according to time sequence, and the extraction operation of the maximum frequency index value of the channel is executed. A counter of 0-n _ delay-1 for increasing cycle is designed, and the counting range is 0-n _ delay-1. And when the counter = n _ delay-1, performing state transition. The state machine operates circularly to obtain a one-dimensional frequency index value sequence, and the sequence is obtained according to the time sequence of each channel and each window, so that the sequence represents a time-frequency index value curve of the beat signal.

On the basis, the beat frequency can be calculated according to the FFT point number N and the FPGA running clock frequency fs

The time-frequency index value curve can be converted into a time-frequency curve, and the frequency stable value in the curve is the stable frequency of the beat frequency signal.

It can be understood that all key signals in the operation process in the FPGA can be captured and monitored on line through the ILA on-line logic analyzer in the FPGA.

On the basis of obtaining time-frequency data, such as the time-frequency curve mentioned above, various applications can be performed. For example, when the set target is in a stationary state, the distance between the FMCW lidar and the set target may be calculated according to the following formula:

d＝cTf _iF /(4BW)

wherein f is _iF The stable frequency in the time frequency data may be a value of an interval where the time frequency data is kept stable, and the value of the interval where the time frequency data is kept stable may be a maximum value of the time frequency data at the distance; BW is the bandwidth range of the tone of the transmitted optical signal; t is the frequency modulation period of the emitted light signal; and c is the speed of light.

For another example, when the set target is in a moving state, the moving speed of the set target may be calculated according to the following formula:

fd＝2vf/c

In order to more clearly illustrate the implementation process of the embodiment of the present invention, the following scenario is illustrated as an example.

Please refer to fig. 10, which is a flowchart of distance measurement and speed measurement based on FMCW lidar. The FMCW laser radar transmits frequency modulation continuous wave laser, the laser hits a target to be reflected, the FMCW laser radar receives an optical signal reflected by the target, and coherent beat frequency is carried out on the reflected optical signal and the transmitted optical signal to obtain a beat frequency signal.

The time frequency data is calculated in real time based on an FPGA (Field Programmable Gate Array). Exemplarily, the following steps are carried out:

defining a function of the beat signal as x (t), defining a window function w (t), and shifting the window function to the beginning of the beat signal and multiplying the beat signal to obtain a function expression y (t) = x (t) · w (t-a) after the beat signal is windowed. Where a is the function displacement.

Performing Fourier transform on each windowed beat signal by adopting the following formula:

the spectral distribution X (ω) of the segmentation sequence is thus obtained. Since the signal is a discrete point sequence in practical engineering applications, a frequency spectrum sequence S [ N ] is obtained. Defining S (ω, a) and representing the result of fourier transforming the primitive function with the center of the window function as a, namely:

corresponding to a discrete scene, S [ omega, a ] represents a result sequence obtained by performing Fourier transform on the obtained segmented sequence, and is a two-dimensional matrix, and each column represents the windowing of signals at different positions.

After the fourier transform operation for each segment is completed, the window function is moved to the next. For example, after the fourier transform operation of the first segment is completed, the window function is moved to a1, and the interval from a0 to a1 is called a sliding window interval, which is smaller than the window width, so as to ensure that there is a certain overlap between the two previous and next windows. Under the condition of fixed window size, the smaller the sliding window interval is, the larger the overlapping part is, and the higher the time resolution of the finally obtained time-frequency analysis measurement result is.

And aiming at each beat frequency signal, executing the steps of multiplying the function of the beat frequency signal by a window function, carrying out Fourier transform on the result of the function windowing and moving the window function, thereby obtaining an S ([ omega n, an ]) two-dimensional matrix sequence.

And (2) performing energy analysis on frequency spectrum components of the result in each window in the S ([ omega n, an ]) two-dimensional matrix sequence, searching for a peak value to obtain a frequency point with the maximum energy, and then arranging the frequency points with the maximum energy in all the windows according to the time sequence of the corresponding windows to obtain a time-frequency curve of the beat signal so as to obtain the stable frequency of the beat signal.

In the case of a relatively stationary object, the coherent beat frequency model of the emitted light and the reflected light from the relatively stationary object is as follows:

as shown in fig. 11, it is a theoretical model (relative to a stationary target) based on the time-frequency curve of the FMCW lidar beat signal. Coherent beat frequency of the emitted light and the reflected light of the relatively static object generates beat frequency signals, and the functional expression of the laser signals emitted by the FMCW laser radar is defined as

Wherein f is ₀ Is the starting frequency of the frequency modulated laser signal,

is the FM slope, T is the FM period, BW is the FM bandwidth range, tau = Tf _IF /(2 BW) is the time (time of flight) for the emitted light to return after reflection by the target, i.e., the target reflected light has a time delay difference of τ with respect to the emitted light, f _IF Is the stable frequency of the beat signal.

The optical path difference between the emitted light and the reflected light results in the time delay difference between the emitted light and the reflected light reaching the photodetector inside the FMCW lidar, and the frequency function curves of the emitted light and the reflected light are shown in fig. 11. In the graph, the solid line represents the curve of the optical frequency function of the emitted light, the dotted line represents the curve of the optical frequency function of the target reflected light, and the stable value f of the beat frequency is obtained in the ith period part time interval (i-1), T + tau < T < (iT-T/2) _IF From the relationship between the optical length, the speed of light and the time

Distance can be calculated

The lower curve in FIG. 11 is the time-frequency curve of the beat signal, the time-frequency curve and f _IF The value of (b) can be obtained by the time-frequency analysis method described above.

In the case where the target is in a relative motion state, as shown in fig. 12, the target is a theoretical model (relative motion target) based on the FMCW lidar beat signal time-frequency curve. Coherent beating of the emitted light and the reflected light from a relatively moving object to obtain a beat signal, the model of the relatively moving object being distinguished from the model of the relatively stationary object in that the movement of the object causes a doppler shift in the reflected light, the doppler frequency f being the frequency at which the reflected light is shifted _d And =2 × v × f/c, wherein v is the target relative motion speed, f is the laser carrier frequency, and c is the speed of light. The stable beat frequency f of the first half (0-T/2) of the corresponding beat signal _IF1 Beat frequency with relatively stationary objectsStable frequency f _IF The relationship is f _IF1 ＝f _IF -f _d Beat frequency stabilization frequency f of the second half modulation period (T/2 ~ T) _IF2 And f _IF The relationship is f _IF2 ＝f _IF +f _d F is measured by the time-frequency analysis and measurement method _IF1 And f _IF2 According to the above formula, f can be further calculated _IF And fd, and further calculating the target distance and the movement speed.

In order to perform the corresponding steps in the above embodiments and various possible modes, an implementation mode of the beat signal analysis device is given below. Referring to fig. 13, fig. 13 is a functional block diagram of a beat signal analyzer 140 according to an embodiment of the invention, where the beat signal analyzer 140 can be applied to the electronic device 100 shown in fig. 1. It should be noted that the basic principle and the generated technical effect of the beat signal analyzing device 140 provided in the present embodiment are the same as those of the above embodiments, and for the sake of brief description, no part of the present embodiment is mentioned, and corresponding contents in the above embodiments may be referred to. The beat signal analysis device 140 includes a signal processing module 141 and a signal analysis module 142.

The signal processing module 141 is configured to perform multi-channel delay and multiplexing on a signal to be processed to obtain multiple beat signals with delay differences in each channel and cascaded in each channel, and perform windowing on the beat signal in each channel.

The signal analysis module 142 is configured to perform FFT operation on each beat frequency signal after the windowing processing to obtain a plurality of FFT operation result data streams; analyzing and obtaining a channel result corresponding to the beat signal of each channel based on each FFT operation result data stream; and processing the channel results according to a time delay sequence relation to obtain time-frequency data of the signals to be processed.

On the basis, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a computer program, and when the computer program runs, the electronic device where the computer-readable storage medium is located is controlled to execute the beat signal analysis method.

By adopting the scheme in the embodiment of the invention, the time-frequency synchronous analysis and measurement can be carried out on the FMCW laser radar beat frequency signal, thereby solving the problem that the time domain information of the beat frequency signal cannot be embodied in the result of the traditional direct FFT frequency measurement method. The beat frequency signal time-frequency analysis method adopted by the embodiment of the invention can flexibly adjust the parameters such as the number of parallel channels, the time delay among the channels, the windowing width, the point number and the like according to different modulation bandwidths and modulation periods of the FMCW laser radar, thereby ensuring that the time-frequency curve of the beat frequency signal can give consideration to both the time resolution and the frequency resolution and providing effective data support for realizing the functions of ranging and speed measurement of the FMCW laser radar.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method of beat signal analysis, comprising:

performing multi-channel time delay and multiplexing processing on a signal to be processed to obtain a plurality of beat frequency signals of which each channel has time delay difference and is cascaded;

windowing the beat frequency signal of each channel;

analyzing and obtaining a channel result corresponding to the beat signal of each channel based on each FFT operation result data stream;

2. The beat signal analysis method according to claim 1, further comprising the step of obtaining the signal to be processed, the step comprising:

obtaining a beat frequency signal generated by coherent beat frequency of a transmission light signal and a reflection light signal of the FMCW laser radar; the transmitting light signal is a frequency modulation continuous wave laser signal transmitted by the FMCW laser radar, and the reflecting light signal is a light signal which is received by the FMCW laser radar and is reflected after the frequency modulation continuous wave laser reaches a set target;

3. The beat signal analysis method according to claim 1 or 2, wherein the step of performing multi-channel delay and multiplexing on the signal to be processed to obtain a plurality of beat signals with delay difference and cascade connection of each channel comprises:

4. The beat signal analysis method according to claim 3, wherein the step of windowing the beat signal of each channel comprises:

generating a data sequence of a Hamming window;

adjusting the data bit width of the data sequence to be a designated bit width, and then taking the data bit width as an initialization file of the ROM in the FPGA;

multiplying the hamming window data streams with the beat frequency signals of the channels to obtain the windowed beat frequency signals of each channel.

5. The method of claim 4, wherein the step of performing FFT operation on each of the windowed beat signals to obtain a plurality of FFT operation result data streams comprises:

respectively calculating the square of a frequency domain amplitude real part signal and the square of an imaginary part signal of the beat frequency signal based on multipliers added to corresponding channels in the FPGA aiming at the beat frequency signal of each channel after windowing;

the step of processing the result of each channel according to the time-delay sequence relation to obtain the time-frequency data of the signal to be processed comprises the following steps:

6. The beat signal analysis method according to claim 5, wherein a counter for increasing cycles and a state machine having the same number of states as the number of channels are provided in the FPGA, wherein each state of the state machine corresponds to each channel arranged in time sequence;

under the condition that the counter is at the maximum value, state transition is carried out on the basis of the state machine, and the maximum frequency index value corresponding to the channel corresponding to the state is taken to obtain a one-dimensional serial frequency index value sequence;

7. The beat signal analysis method according to claim 2, wherein in the case where the set target is in a stationary state, the method further comprises calculating a distance between the FMCW lidar and the set target according to the following formula:

d＝cTf _iF /(4BW)

wherein, f _iF The stable frequency in the time frequency data is obtained; BW is a bandwidth range of the modulation frequency of the emission light signal; t is the frequency modulation period of the emitted light signal; c is the speed of light;

in the case that the set target is in a moving state, the method further includes calculating a moving speed of the set target according to the following formula:

fd＝2vf/c

wherein fd is the Doppler frequency obtained by analyzing the time-frequency data; v is the moving speed of the set target; f is the laser carrier frequency; and c is the speed of light.

8. A beat signal analysis apparatus, comprising:

the signal analysis module is used for carrying out FFT operation on each beat frequency signal subjected to windowing processing to obtain a plurality of FFT operation result data streams; analyzing and obtaining a channel result corresponding to the beat signal of each channel based on each FFT operation result data stream; processing the channel results according to a time delay sequence relation to obtain time-frequency data of the signals to be processed;

9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the beat signal analysis method of any of claims 1 to 7 when executing the program.

10. A computer-readable storage medium, comprising a computer program, which when executed controls an electronic device where the computer-readable storage medium is located to perform the beat signal analysis method according to any one of claims 1 to 7.