CN118275788A

CN118275788A - Parameter estimation method, device, equipment and storage medium

Info

Publication number: CN118275788A
Application number: CN202410703982.4A
Authority: CN
Inventors: 魏急波; 辜方林; 张晓瀛; 侯茂斌; 熊俊; 赵海涛
Original assignee: National University of Defense Technology
Current assignee: National University of Defense Technology
Filing date: 2024-06-03
Publication date: 2024-07-02

Abstract

The application discloses a parameter estimation method, a device, equipment and a storage medium, which relate to the technical field of signal and information processing and comprise the following steps: the method comprises the steps of obtaining an electromagnetic signal to be estimated, carrying out segmentation processing to obtain a first target signal, and carrying out delay processing and segmentation processing to obtain a second target signal; performing fast Fourier transform on the first target signal and the second target signal to obtain a first time frequency spectrum and a second time frequency spectrum; determining correlation values of the first time spectrum and the second time spectrum to determine a delay time spectrum of the electromagnetic signal to be estimated; normalizing the delay frequency spectrum based on a preset normalization rule, determining a plurality of detection thresholds of preset signal to noise ratios based on the obtained target delay frequency spectrum, detecting target frequency points of the target delay frequency spectrum according to the detection thresholds, and carrying out parameter estimation based on detection results. By normalizing the frequency spectrum during signal, the detection threshold can be reasonably set for detection under the condition of different gains, which is beneficial to parameter estimation in complex electromagnetic environment.

Description

Parameter estimation method, device, equipment and storage medium

Technical Field

The present invention relates to the field of signal and information processing technologies, and in particular, to a method, an apparatus, a device, and a storage medium for parameter estimation.

Background

With the increase of wireless frequency-using devices, particularly in modern warfare electronic countermeasures, military communication and other wireless games, electromagnetic environments are more and more complex, and how to represent complex electromagnetic environments with simple parameters and achieve efficient detection of representation parameters is important. In fact, the electromagnetic environment is a comprehensive effect formed by the signals working in different frequency bands, so that accurate estimation of characteristic parameters of the signals in the range of the frequency band of interest is realized, and parameter characterization of the electromagnetic environment can be realized.

In the electronic reconnaissance process, how to finish radar sorting according to signals collected by an electronic warfare (EW, electronic Warfare) receiver is a critical problem, and the core is to realize feature extraction of the signals collected by the electronic warfare receiver, because radar is usually a Pulse signal, the radar is usually characterized by a Pulse description word (PDW, pulse description word), and the Pulse description word includes parameter coding information such as a carrier frequency (CF, carrier frequency), a time of arrival (TOA, time of arrive), a Pulse Width (PW), a Pulse amplitude (PA, pulse amplitude) and the like of each Pulse, so that a digital processor can be used to analyze, sort and identify an input signal. Based on the detection, the radar sorting is completed according to the parameters obtained by detection.

Similarly, in the wireless communication process, especially along with the development of cognitive radio technology in recent years, the realization of sensing of a complex electromagnetic environment is a key and precondition for dynamic spectrum access, and the traditional complex electromagnetic environment sensing usually only utilizes means such as energy detection to complete the detection of whether signals exist or not, so that the feature description granularity of interference signals in the complex electromagnetic environment is very coarse, and the novel technologies such as dynamic spectrum access and the like are difficult to effectively support and realize, thereby improving the spectrum utilization efficiency and anti-interference capability of a system. Aiming at the problems, how to efficiently perform parameter estimation and realize accurate description of a complex electromagnetic environment is a problem to be solved in the field.

Disclosure of Invention

Accordingly, the present invention is directed to a method, an apparatus, a device, and a storage medium for parameter estimation, which can utilize a signal delay time spectrum to perform signal feature description, improve the signal feature description effect in a complex electromagnetic environment, facilitate supporting and implementing technologies such as dynamic spectrum access, and improve anti-interference capability, and through normalization of the signal delay time spectrum, reasonably set detection thresholds for detection under different gain conditions, and facilitate parameter estimation in the complex electromagnetic environment. The specific scheme is as follows:

in a first aspect, the present application provides a parameter estimation method, including:

Acquiring an electromagnetic signal to be estimated, carrying out sectional processing on the electromagnetic signal to be estimated to obtain a first target signal, carrying out delay processing on the electromagnetic signal to be estimated, and carrying out sectional processing on the delayed signal to obtain a second target signal;

performing fast Fourier transform on the first target signal and the second target signal to obtain a first time spectrum and a second time spectrum corresponding to the electromagnetic signal to be estimated;

Determining correlation values of the first time spectrum and the second time spectrum according to a preset correlation function, so as to determine a time-delay frequency spectrum of the electromagnetic signal to be estimated based on the correlation values;

Normalizing the time delay frequency spectrum based on a preset normalization rule, determining a plurality of detection thresholds corresponding to preset signal-to-noise ratios based on a target time delay frequency spectrum obtained after normalization, detecting target frequency points in the target time delay frequency spectrum according to the detection thresholds, and estimating parameters based on detection results.

Optionally, before the detecting, according to the detection threshold, the target frequency point in the delay frequency spectrum further includes:

Detecting a target signal determined based on the electromagnetic signal to be estimated in the target delay time spectrum; if the target signals are detected to exist in the frequency points corresponding to the continuous first preset number of signal segments in the target delay frequency spectrum, the currently detected frequency points are used as target frequency points, so that the target frequency points in the target delay frequency spectrum are detected according to the detection threshold.

Optionally, the performing parameter estimation based on the detection result includes:

Performing threshold detection on the continuous first preset number of signal segments in the target delay time frequency spectrum according to the detection threshold;

If the threshold detection of the first preset number of signal segments is passed and the frequency point detected currently is the frequency point passed by the first threshold detection, determining that the target signal exists on the frequency point detected currently, and taking the current time as the arrival time of the electromagnetic signal to be estimated.

if the threshold detection of the first preset number of signal segments is passed, selecting a second preset number of signal segments from the first preset number of signal segments, determining an average value of the second preset number of signal segments, and determining the average value as the pulse amplitude of the electromagnetic signal to be estimated.

Optionally, the parameter estimation based on the detection result further includes:

Continuously performing threshold detection on the continuous first preset number of signal segments in the target delay time spectrum according to the detection threshold;

if the threshold detection of the first preset number of signal segments is not passed, determining the current time as the vanishing time of the electromagnetic signal to be estimated, and determining the pulse width of the electromagnetic signal to be estimated according to the arrival time and the vanishing time.

determining the frequency of the frequency point passing through the first threshold detection as the initial frequency of the electromagnetic signal to be estimated;

And continuously performing threshold detection on the continuous first preset number of signal segments in the target delay time frequency spectrum according to the detection threshold, determining the frequency of the frequency point passing through the last detected threshold detection as the cut-off frequency of the electromagnetic signal to be estimated, taking the difference between the starting frequency and the cut-off frequency as the frequency bandwidth of the electromagnetic signal to be estimated, and taking the centers of the starting frequency and the cut-off frequency as the center frequency of the electromagnetic signal to be estimated.

Optionally, normalizing the time-delay frequency spectrum based on a preset normalization rule includes:

and determining the spectrum median of the time-delay spectrum according to a preset median calculation module so as to normalize the time-delay spectrum according to the spectrum median.

In a second aspect, the present application provides a parameter estimation apparatus, comprising:

The signal processing module is used for acquiring an electromagnetic signal to be estimated, carrying out sectional processing on the electromagnetic signal to be estimated to obtain a first target signal, carrying out delay processing on the electromagnetic signal to be estimated, and carrying out sectional processing on the delayed signal to obtain a second target signal;

The first time spectrum determining module is used for performing fast Fourier transform on the first target signal and the second target signal to obtain a first time spectrum and a second time spectrum corresponding to the electromagnetic signal to be estimated;

The second time spectrum determining module is used for determining the correlation value of the first time spectrum and the second time spectrum according to a preset correlation function so as to determine the delay time spectrum of the electromagnetic signal to be estimated based on the correlation value;

And the parameter estimation module is used for normalizing the time delay frequency spectrum based on a preset normalization rule, determining a plurality of detection thresholds corresponding to preset signal-to-noise ratios based on the target time delay frequency spectrum obtained after normalization, detecting target frequency points in the target time delay frequency spectrum according to the detection thresholds, and carrying out parameter estimation based on detection results.

In a third aspect, the present application provides an electronic device comprising a processor and a memory; wherein the memory is configured to store a computer program that is loaded and executed by the processor to implement the aforementioned parameter estimation method.

In a fourth aspect, the present application provides a computer readable storage medium storing a computer program which when executed by a processor implements the aforementioned parameter estimation method.

In the method, an electromagnetic signal to be estimated is obtained, the electromagnetic signal to be estimated is subjected to sectional processing to obtain a first target signal, the electromagnetic signal to be estimated is subjected to delay processing, and the delayed signal is subjected to sectional processing to obtain a second target signal; performing fast Fourier transform on the first target signal and the second target signal to obtain a first time spectrum and a second time spectrum corresponding to the electromagnetic signal to be estimated; determining correlation values of the first time spectrum and the second time spectrum according to a preset correlation function, so as to determine a time-delay frequency spectrum of the electromagnetic signal to be estimated based on the correlation values; normalizing the time delay frequency spectrum based on a preset normalization rule, determining a plurality of detection thresholds corresponding to preset signal-to-noise ratios based on a target time delay frequency spectrum obtained after normalization, detecting target frequency points in the target time delay frequency spectrum according to the detection thresholds, and estimating parameters based on detection results. Therefore, the signal characteristic description can be performed by utilizing the signal delay time spectrum, the problem of coarse granularity of the characteristic description of the interference signal in the complex electromagnetic environment caused by the fact that whether the signal is detected by utilizing means such as energy detection is avoided, the characteristic description effect of the signal in the complex electromagnetic environment is improved, the technology such as dynamic spectrum access is supported and realized, the anti-interference capability is improved, the detection threshold can be reasonably set for detection under the condition of different gains through normalization of the spectrum when the signal is performed, and the parameter estimation in the complex electromagnetic environment is facilitated.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a parameter estimation method provided by the application;

Fig. 2 is a schematic diagram of a signal spectrum under an oversampling condition according to the present application;

FIG. 3 is a graph of time spectrum under different signal-to-noise ratio conditions according to the present application;

FIG. 4 is a flowchart of a normalization process according to the present application;

FIG. 5 is a graph showing the median distribution of a time-lapse spectrum according to the present application;

FIG. 6 is a graph of a delay time spectrum based on median normalization under different signal to noise ratio conditions;

FIG. 7 is a flowchart of a specific parameter estimation method according to the present application;

FIG. 8 is a flowchart of a normalized parameter estimation method provided by the present application;

FIG. 9 is a flow chart of estimating time of arrival parameters according to the present application;

FIG. 10 is a flow chart of pulse amplitude parameter estimation according to the present application;

FIG. 11 is a flowchart of a pulse width parameter estimation method according to the present application;

FIG. 12 is a flowchart of a pulse frequency parameter estimation method according to the present application;

FIG. 13 is a schematic diagram of a parameter estimation device according to the present application;

fig. 14 is a block diagram of an electronic device according to the present application.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Along with the development of the cognitive radio technology, the realization of the perception of the complex electromagnetic environment is a key and precondition for dynamic spectrum access, but the traditional perception of the complex electromagnetic environment usually only utilizes means such as energy detection to finish the detection of whether signals exist or not, and is difficult to effectively support and realize new technologies such as dynamic spectrum access. The application can utilize the signal delay frequency spectrum to carry out the characteristic description of the signal, improves the characteristic description effect of the signal in the complex electromagnetic environment, supports the technologies such as dynamic frequency spectrum access and the like, and reasonably sets the detection threshold to carry out detection under the condition of different gains by normalizing the frequency spectrum when carrying out the signal, thereby being beneficial to parameter estimation in the complex electromagnetic environment.

Referring to fig. 1, the embodiment of the invention discloses a parameter estimation method, which comprises the following steps:

step S11, an electromagnetic signal to be estimated is obtained, segmentation processing is carried out on the electromagnetic signal to be estimated to obtain a first target signal, delay processing is carried out on the electromagnetic signal to be estimated, and segmentation processing is carried out on the signal after delay processing to obtain a second target signal.

In this embodiment, an electromagnetic signal to be estimated that needs to be subjected to parameter estimation is first obtained, then the electromagnetic signal to be estimated is subjected to segmentation processing to obtain a first target signal, and after the electromagnetic signal to be estimated is subjected to delay processing, a signal obtained after the delay processing is subjected to segmentation processing to obtain a second target signal. It is to be understood that the segmentation process and the delay process in this embodiment are not particularly limited herein, and may satisfy the corresponding effects.

And step S12, performing fast Fourier transform on the first target signal and the second target signal to obtain a first time spectrum and a second time spectrum corresponding to the electromagnetic signal to be estimated.

In this embodiment, it should be noted that, when the signal is subjected to spectrum analysis, the spectrum analysis is an effective means for realizing estimation of parameters included in the pulse descriptors, and classical spectrum estimation includes a direct method and an indirect method, where the direct method is obtained by directly calculating the spectrum of the signal by using fast fourier (Fast fourier transform, FFT) and multiplying the obtained spectrum by the conjugate of the spectrum; the indirect method is to calculate the autocorrelation function of the signal first and then calculate the autocorrelation function by using FFT. On the basis, the processing modes such as windowing and the like are further considered, the influence of spectrum leakage and the like is reduced, and other improved spectrum analysis methods including Bartlett method, welch method and the like can be adopted. Therefore, in this embodiment, fast fourier transformation is required to be performed on the first target signal and the second target signal, so as to obtain a first time spectrum and a second time spectrum corresponding to the electromagnetic signal to be estimated.

It will be appreciated that the sampling rate (sampling clock) of the signal is critical in the signal spectrum analysis process, and in practical systems, sampling is typically performed using a sampling clock of at least 2 times the signal bandwidth, which is determined by the bandwidth of the front-end analog filter for a scout receiver, according to the nyquist sampling theorem. Under the above constraints, the time spectrum of the received signal is shown in fig. 2. In fig. 2, the number of FFT points is 256 points in the signal spectrum diagram under the condition of 4 times oversampling, and it can be seen that the number of FFT points in the signal spectrum occupation region is about 64 points, and the rest part only has noise, and the result is that the frequency spectrum leakage exists due to the FFT operation and the signal is subjected to shaping filtering. According to the time spectrum obtained by intercepting a certain piece of data for the received signal in fig. 2, the time spectrum of the corresponding data is obtained by utilizing the continuous multi-section received signal, and the splicing is performed so as to finish the time spectrum analysis of the signal subsequently.

Step S13, determining correlation values of the first time spectrum and the second time spectrum according to a preset correlation function, so as to determine a delay time spectrum of the electromagnetic signal to be estimated based on the correlation values.

In this embodiment, correlation values of the first time spectrum and the second time spectrum are determined according to a preset correlation function, so as to determine a time-delay time spectrum of the electromagnetic signal to be estimated based on the determined correlation values, so as to perform time-spectrum analysis after normalization processing.

And step S14, normalizing the time delay frequency spectrum based on a preset normalization rule, determining a plurality of detection thresholds corresponding to preset signal-to-noise ratios based on the target time delay frequency spectrum obtained after normalization, detecting target frequency points in the target time delay frequency spectrum according to the detection thresholds, and estimating parameters based on detection results.

In this embodiment, as shown in fig. 3, a time-spectrum curve of a time spectrum under different signal-to-noise ratios of the received signals is disclosed. It can be appreciated that in the detection or estimation of parameters, the core is to detect which frequency points have signals and which frequency points have no signals from the time spectrum. It can be seen that the core of the correct detection is to reasonably set the detection threshold, and if the detection threshold is not processed for the time spectrum, different thresholds need to be set under different signal-to-noise ratio (receiving gain) conditions, which is difficult to achieve in a practical system. Therefore, the present embodiment addresses the above-described problem by presetting the median calculation module to utilize the median of the time spectrum as the normalized reference normalized time spectrum, as shown in fig. 4.

It can be understood that when the receiving end samples the signal, the sampling frequency is at least more than 2 times of the bandwidth of the received signal, accordingly, at least half of the area after the FFT of the received signal has noise only, and from the time spectrum and the median of each segment of the signal after the segment processing of the acquired signal shown in fig. 5, whether the segment of the acquired signal contains the target signal or not, the median of the time spectrum is basically maintained unchanged and reflects the noise level, so that the median of the time spectrum is suitable for the normalization reference of the time spectrum. As shown in fig. 6, based on the delay frequency spectrum based on the median normalization under different signal-to-noise ratio conditions, it can be seen that the normalized delay frequency spectrum is basically consistent in noise section and is irrelevant to signal-to-noise ratio, and under the condition of existence of a target signal area and different signal-to-noise ratios, the normalized time spectrum reflects the signal-to-noise ratio of the current received signal, so that the normalized time spectrum has a linear corresponding relation with the signal-to-noise ratio (pulse amplitude) of the received target signal, thereby being beneficial to the subsequent parameter estimation of the signal. Through the technical scheme, the frequency spectrum median of the time-delay frequency spectrum is determined according to the preset median calculation module, so that the time-delay frequency spectrum is normalized according to the frequency spectrum median, and the detection threshold adapting to different signal-to-noise ratio conditions is obtained on the basis, so that the correct detection of the target frequency point in the time-delay frequency spectrum is realized.

It should be noted that, the target frequency point in the present embodiment is a frequency point that satisfies a preset condition, so before the target frequency point in the delay time spectrum is detected according to the detection threshold, the target signal determined based on the electromagnetic signal to be estimated in the target delay time spectrum is detected first; if the target signals are detected to exist in the frequency points corresponding to the continuous first preset number of signal segments in the target delay frequency spectrum, the currently detected frequency points are used as target frequency points, so that the target frequency points in the target delay frequency spectrum are detected according to a detection threshold. By setting the target frequency point, the influence of factors such as signal burrs can be reduced, and the effect of parameter estimation is improved.

Through the technical scheme, the method comprises the steps of obtaining an electromagnetic signal to be estimated, carrying out sectional processing on the electromagnetic signal to be estimated to obtain a first target signal, carrying out delay processing on the electromagnetic signal to be estimated, and carrying out sectional processing on a signal after delay processing to obtain a second target signal; performing fast Fourier transform on the first target signal and the second target signal to obtain a first time spectrum and a second time spectrum corresponding to the electromagnetic signal to be estimated; determining correlation values of the first time spectrum and the second time spectrum according to a preset correlation function, so as to determine a time-delay frequency spectrum of the electromagnetic signal to be estimated based on the correlation values; and determining the spectrum median of the delay time spectrum according to a preset median calculation module, normalizing the delay time spectrum according to the spectrum median, determining a plurality of detection thresholds corresponding to preset signal-to-noise ratios based on a target delay time spectrum obtained after normalization, detecting target frequency points in the target delay time spectrum according to the detection thresholds, and estimating parameters based on detection results. Therefore, the characteristic description of the signal can be carried out by utilizing the signal delay time spectrum, the characteristic description effect of the signal in the complex electromagnetic environment is improved, the technologies such as dynamic spectrum access and the like are supported and realized, the anti-interference capability is improved, the detection threshold can be reasonably set for detection under the condition of different gains by normalizing the signal time spectrum, the parameter estimation in the complex electromagnetic environment is facilitated, the influence of factors such as signal burrs can be reduced by setting the target frequency point, and the effect of the parameter estimation is improved.

Based on the above embodiment, the present application can utilize the signal delay frequency spectrum to perform signal characterization, and perform parameter estimation in a complex electromagnetic environment, and the process of parameter estimation will be described in detail in this embodiment. Referring to fig. 7, the embodiment of the application discloses a specific parameter estimation method, which includes:

Step S21, carrying out threshold detection on a first continuous preset number of signal segments in a target delay time frequency spectrum according to a detection threshold; if the threshold detection of the first preset number of signal segments is passed and the frequency point detected currently is the frequency point passed by the first threshold detection, determining that a target signal exists on the frequency point detected currently, and taking the current time as the arrival time of the electromagnetic signal to be estimated.

In this embodiment, as shown in fig. 8, the idea of completing radar sorting by using PDW parameters in electronic warfare is used, and complex electromagnetic environment characterization faced by cognitive wireless communication is represented by using parameter set Signal descriptors (Signal description word, SDW) similar to PDW, including carrier frequency, arrival time, signal width (SIGNAL WIDTH, SW) and Signal Amplitude (SA), and accurate detection and estimation of these parameters are completed. Firstly, calculating the time delay spectrum of a received signal, wherein the basic idea is to segment the received signal, calculate the spectrum of each segment of signal and the time delay spectrum thereof by FFT, and then calculate the correlation value. Then, the normalization method according to the above embodiment normalizes the obtained delay frequency spectrum, and obtains detection thresholds adapting to different signal-to-noise ratio conditions on the basis of the normalization method, so as to realize correct detection of the frequency point of the target signal in the time-lapse frequency spectrum. Finally, according to the definition of TOA, PW (SW), PA (SA), CF and other parameters, the estimation of the corresponding parameter values is completed.

Based on the definition of the target frequency point in the above embodiment, the arrival time of the target signal is estimated first. The target signal arrival time is defined as the time when the target signal exists in the frequency point for the first time, and in order to reduce the influence of factors such as signal burrs, the present invention agrees that only the target signal exists in the corresponding frequency point in the time spectrum of the continuous P-section signal, the current frequency point is considered to exist in the target signal. Thus, as shown in fig. 9, the continuous P signal segments in the target delay time spectrum are subjected to threshold detection according to the detection threshold; if the threshold detection of the P signal segments passes, and the frequency point detected at present is the frequency point passing the threshold detection, judging that a target signal exists on the frequency point detected at present, and taking the current time as the arrival time of the electromagnetic signal to be estimated.

Step S22, carrying out threshold detection on the continuous first preset number of signal segments in the target delay time spectrum according to the detection threshold; if the threshold detection of the first preset number of signal segments is passed, selecting a second preset number of signal segments from the first preset number of signal segments, determining an average value of the second preset number of signal segments, and determining the average value as the pulse amplitude of the electromagnetic signal to be estimated.

In this embodiment, the target signal amplitude (strength) is defined as the frequency point where the target signal exists, and the signal-to-noise ratio of the received signal. In order to reduce the influence of random factors and increase the reliability of estimation parameters, in the condition that the target signal exists in the frequency point is detected in the embodiment, the normalized time spectrum average value of the corresponding frequency point in the time spectrum of the continuous L-section signal is adopted as the amplitude (intensity) of the target signal of the current frequency point. As shown in fig. 10, after threshold detection is performed on continuous P signal segments in the target delay time spectrum according to a detection threshold; if the threshold detection of the P signal segments is passed, L signal segments are selected from the P signal segments, the average value of the L signal segments is determined, and the average value is determined as the pulse amplitude of the electromagnetic signal to be estimated.

Step S23, continuously performing a step of threshold detection on the continuous first preset number of signal segments in the target delay time spectrum according to the detection threshold; if the threshold detection of the first preset number of signal segments is not passed, determining the current time as the vanishing time of the electromagnetic signal to be estimated, and determining the pulse width of the electromagnetic signal to be estimated according to the arrival time and the vanishing time.

In this embodiment, the target signal width is defined as the starting time of detecting that the target signal exists in the frequency point and the time of detecting that the target signal of the corresponding frequency point disappears, and similarly, only if the target signal is not detected in the corresponding frequency point in the time spectrum of the continuous P-segment signal, the target signal of the current frequency point is considered to have disappeared. As shown in fig. 11, the step of performing threshold detection on consecutive P signal segments in the target delay time spectrum according to the detection threshold is continuously performed; if the threshold detection of the P signal segments is not passed, determining the current time as the vanishing time of the electromagnetic signal to be estimated, and determining the pulse width of the electromagnetic signal to be estimated according to the arrival time and the vanishing time.

Step S24, determining the frequency of the frequency point passing through the first threshold detection as the initial frequency of the electromagnetic signal to be estimated; and continuously performing threshold detection on the continuous first preset number of signal segments in the target delay time frequency spectrum according to the detection threshold, determining the frequency of the frequency point passing through the last detected threshold detection as the cut-off frequency of the electromagnetic signal to be estimated, taking the difference between the starting frequency and the cut-off frequency as the frequency bandwidth of the electromagnetic signal to be estimated, and taking the centers of the starting frequency and the cut-off frequency as the center frequency of the electromagnetic signal to be estimated.

In this embodiment, the target signal frequency parameter includes two parameters, i.e., a center frequency (or carrier frequency, CF) and a frequency width. Therefore, in this embodiment, the frequency point where the time spectrum of the first continuous P-segment signal detects that the target signal exists is taken as the starting frequency, and the frequency point where the time spectrum of the last adjacent continuous P-segment signal detects that the target signal exists is regarded as the cut-off frequency. The difference between the cut-off frequency and the initial frequency is the frequency bandwidth, and the center of the cut-off frequency and the initial frequency is the center frequency. As shown in fig. 12, determining the frequency of the frequency point passing through the first threshold detection as the initial frequency of the electromagnetic signal to be estimated; and continuously performing threshold detection on the continuous P signal segments in the target delay time frequency spectrum according to the detection threshold, determining the frequency of the frequency point passing through the last detected threshold detection as the cut-off frequency of the electromagnetic signal to be estimated, taking the difference between the starting frequency and the cut-off frequency as the frequency bandwidth of the electromagnetic signal to be estimated, and taking the centers of the starting frequency and the cut-off frequency as the center frequency of the electromagnetic signal to be estimated.

In this embodiment, a plurality of detection thresholds corresponding to preset signal-to-noise ratios are determined based on a target delay spectrum obtained by normalizing a delay spectrum with a median of the spectrum, target frequency points in the target delay spectrum are detected according to the detection thresholds, and parameter estimation such as carrier frequency, arrival time, signal width, signal amplitude and the like is performed based on detection results. The signal characteristic description can be performed by utilizing the normalized signal delay time spectrum, the characteristic description effect of the signal in the complex electromagnetic environment is improved, the influence of factors such as signal burrs can be reduced through setting the target frequency point, and the effect of parameter estimation is improved.

Referring to fig. 13, the embodiment of the application also discloses a parameter estimation device, which comprises:

the signal processing module 11 is configured to obtain an electromagnetic signal to be estimated, perform segmentation processing on the electromagnetic signal to be estimated to obtain a first target signal, perform delay processing on the electromagnetic signal to be estimated, and perform segmentation processing on the delayed signal to obtain a second target signal;

A first time spectrum determining module 12, configured to perform a fast fourier transform on the first target signal and the second target signal, so as to obtain a first time spectrum and a second time spectrum corresponding to the electromagnetic signal to be estimated;

A second time spectrum determining module 13, configured to determine correlation values of the first time spectrum and the second time spectrum according to a preset correlation function, so as to determine a delay time spectrum of the electromagnetic signal to be estimated based on the correlation values;

The parameter estimation module 14 is configured to normalize the delay time spectrum based on a preset normalization rule, determine detection thresholds corresponding to a plurality of preset signal-to-noise ratios based on a target delay time spectrum obtained after normalization, detect target frequency points in the target delay time spectrum according to the detection thresholds, and perform parameter estimation based on a detection result.

In this embodiment, an electromagnetic signal to be estimated is obtained, the electromagnetic signal to be estimated is subjected to segmentation processing to obtain a first target signal, the electromagnetic signal to be estimated is subjected to delay processing, and the delayed signal is subjected to segmentation processing to obtain a second target signal; performing fast Fourier transform on the first target signal and the second target signal to obtain a first time spectrum and a second time spectrum corresponding to the electromagnetic signal to be estimated; determining correlation values of the first time spectrum and the second time spectrum according to a preset correlation function, so as to determine a time-delay frequency spectrum of the electromagnetic signal to be estimated based on the correlation values; normalizing the time delay frequency spectrum based on a preset normalization rule, determining a plurality of detection thresholds corresponding to preset signal-to-noise ratios based on a target time delay frequency spectrum obtained after normalization, detecting target frequency points in the target time delay frequency spectrum according to the detection thresholds, and estimating parameters based on detection results. Therefore, the signal characteristic description can be performed by utilizing the signal delay time spectrum, the signal characteristic description effect under the complex electromagnetic environment is improved, the technologies such as dynamic spectrum access and the like are supported and realized, the anti-interference capability is improved, and the detection threshold can be reasonably set for detection under the condition of different gains by normalizing the signal time spectrum, so that the parameter estimation under the complex electromagnetic environment is facilitated.

In some embodiments, the parameter estimation module 14 further includes:

the target signal detection unit is used for detecting a target signal determined based on the electromagnetic signal to be estimated in the target delay time spectrum; if the target signals are detected to exist in the frequency points corresponding to the continuous first preset number of signal segments in the target delay frequency spectrum, the currently detected frequency points are used as target frequency points, so that the target frequency points in the target delay frequency spectrum are detected according to the detection threshold.

In some embodiments, the parameter estimation module 14 specifically includes:

A first threshold detection unit, configured to perform threshold detection on the continuous first preset number of signal segments in the target delay time spectrum according to the detection threshold;

And the arrival time detection unit is used for judging that the target signal exists on the frequency point which is currently detected if the threshold detection of the first preset number of signal segments is passed and the frequency point which is currently detected is the frequency point which is passed by the first threshold detection, and taking the current time as the arrival time of the electromagnetic signal to be estimated.

In some embodiments, the parameter estimation module 14 specifically includes:

The second threshold detection unit is used for carrying out threshold detection on the continuous first preset number of signal segments in the target delay time frequency spectrum according to the detection threshold;

and the pulse amplitude detection unit is used for selecting a second preset number of signal segments from the first preset number of signal segments if the threshold detection of the first preset number of signal segments is passed, determining the average value of the second preset number of signal segments, and determining the average value as the pulse amplitude of the electromagnetic signal to be estimated.

In some embodiments, the parameter estimation module 14 further includes:

A third threshold detection unit, configured to continuously perform a step of performing threshold detection on the continuous first preset number of signal segments in the target delay time spectrum according to the detection threshold;

And the pulse width detection unit is used for determining the current time as the vanishing time of the electromagnetic signal to be estimated if the threshold detection of the first preset number of signal segments is not passed, and determining the pulse width of the electromagnetic signal to be estimated according to the arrival time and the vanishing time.

In some embodiments, the parameter estimation module 14 further includes:

The initial frequency determining unit is used for determining the frequency of the frequency point passing through the first threshold detection as the initial frequency of the electromagnetic signal to be estimated;

and the central frequency detection unit is used for continuously carrying out the step of carrying out threshold detection on the continuous first preset number of signal segments in the target delay time frequency spectrum according to the detection threshold, determining the frequency of the frequency point passing through the last detected threshold detection as the cut-off frequency of the electromagnetic signal to be estimated, taking the difference between the starting frequency and the cut-off frequency as the frequency bandwidth of the electromagnetic signal to be estimated and taking the centers of the starting frequency and the cut-off frequency as the central frequency of the electromagnetic signal to be estimated.

In some embodiments, the parameter estimation module 14 specifically includes:

And the time spectrum normalization unit is used for determining the spectrum median of the time delay spectrum according to a preset median calculation module so as to normalize the time delay spectrum according to the spectrum median.

Further, the embodiment of the present application further discloses an electronic device, and fig. 14 is a block diagram of an electronic device 20 according to an exemplary embodiment, where the content of the figure is not to be considered as any limitation on the scope of use of the present application.

Fig. 14 is a schematic structural diagram of an electronic device 20 according to an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input output interface 25, and a communication bus 26. Wherein the memory 22 is configured to store a computer program that is loaded and executed by the processor 21 to implement the relevant steps of the parameter estimation method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in the present embodiment may be specifically an electronic computer.

In this embodiment, the power supply 23 is configured to provide an operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and an external device, and the communication protocol to be followed is any communication protocol applicable to the technical solution of the present application, which is not specifically limited herein; the input/output interface 25 is used for acquiring external input data or outputting external output data, and the specific interface type thereof may be selected according to the specific application requirement, which is not limited herein.

The memory 22 may be a carrier for storing resources, such as a read-only memory, a random access memory, a magnetic disk, or an optical disk, and the resources stored thereon may include an operating system 221, a computer program 222, and the like, and the storage may be temporary storage or permanent storage.

The operating system 221 is used for managing and controlling various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, netware, unix, linux, etc. The computer program 222 may further include a computer program that can be used to perform other specific tasks in addition to the computer program that can be used to perform the parameter estimation method performed by the electronic device 20 disclosed in any of the previous embodiments.

Further, the application also discloses a computer readable storage medium for storing a computer program; wherein the computer program, when executed by a processor, implements the parameter estimation method disclosed previously. For specific steps of the method, reference may be made to the corresponding contents disclosed in the foregoing embodiments, and no further description is given here.

In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, so that the same or similar parts between the embodiments are referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.

Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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 phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The foregoing has outlined rather broadly the more detailed description of the application in order that the detailed description of the application that follows may be better understood, and in order that the present principles and embodiments may be better understood; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.

Claims

1. A method of parameter estimation, comprising:

2. The method of claim 1, further comprising, prior to detecting the target frequency point in the delay spectrum according to the detection threshold:

3. The parameter estimation method according to claim 2, wherein the parameter estimation based on the detection result includes:

4. The parameter estimation method according to claim 2, wherein the parameter estimation based on the detection result includes:

5. The method for estimating parameters according to claim 3, wherein said estimating parameters based on the detection result further comprises:

6. The method for estimating parameters according to claim 3, wherein said estimating parameters based on the detection result further comprises:

7. The method according to any one of claims 1 to 6, wherein normalizing the time-lapse spectrum based on a preset normalization rule comprises:

8. A parameter estimation apparatus, comprising:

9. An electronic device comprising a processor and a memory; wherein the memory is for storing a computer program to be loaded and executed by the processor for implementing the parameter estimation method according to any one of claims 1 to 7.

10. A computer readable storage medium for storing a computer program which, when executed by a processor, implements the parameter estimation method according to any one of claims 1 to 7.