Signal capturing method based on multi-device cooperation and statistic analysis

Abstract

The invention discloses a signal capturing method based on multi-device cooperation and statistic analysis, and belongs to the technical field of signal detection and radio direction finding. The objective of the invention is to solve the problems of low detection probability and high false alarm rate of a single receiver on a burst signal under the conditions of a non-cooperative target and a low signal-to-noise ratio. The method comprises the following steps: step 1, arranging a plurality of devices to perform synchronous data acquisition on a target frequency band; step 2, calculating an autocorrelation function of each device, and selecting the device with the maximum function peak power as a reference device; 3, performing cross-correlation operation on all the devices and the reference device; calculating the statistical characteristic quantity of each cross-correlation function; and 4, comparing each statistical characteristic quantity with a judgment threshold value, and if the statistical quantity is superior to the threshold value, judging that a target signal exists. According to the invention, through combined judgment of multi-device space diversity gain and statistical magnitude, the detection probability of weak burst signals is improved, and the overall false alarm rate of the system is reduced at the same time.

Description

Technical Field

[0001] This invention patent relates to the field of modern radio signal processing, and in particular to an advanced direction finding and positioning technology for complex scenarios with low signal-to-noise ratio and strong interference, specifically involving a signal acquisition method based on multi-device collaboration and statistical analysis. Background Technology

[0002] Rapid, highly sensitive acquisition and accurate parameter estimation of target signals are core prerequisites for passive direction finding and positioning systems. In non-cooperative signal reconnaissance environments, prior information about target signals (such as modulation type, coding scheme, and carrier frequency) is extremely scarce. Furthermore, to evade detection, targets often employ low probability of intercept (LPI) techniques such as spread spectrum and frequency hopping, and deliberately reduce transmit power, leading to a sharp deterioration in the signal-to-noise ratio (SNR) at the receiver, posing a severe challenge to signal acquisition and parameter extraction. To address these challenges, academia and industry have proposed numerous improvement schemes. In signal acquisition, research has primarily focused on improving acquisition strategies. However, these improved methods either suffer from severe performance degradation under low SNR or remain computationally complex, making efficient real-time processing difficult on resource-constrained acquisition equipment. Therefore, existing technologies struggle to simultaneously achieve high acquisition probability, high estimation accuracy, and low computational complexity, necessitating a novel signal processing scheme that can provide efficient and reliable parameter support for subsequent direction finding and positioning in harsh electromagnetic environments.

[0003] Time-domain correlation algorithms are used in direction finding and localization to accurately extract certain parameters, such as time delay estimation in time-difference positioning and phase difference estimation in interferometric direction finding. Existing technologies mainly focus on refining the correlation peaks to make parameter estimation more accurate, often neglecting the difficulty and challenges of signal acquisition in non-cooperative situations. Summary of the Invention

[0004] This invention addresses the insufficient signal detection capability in non-cooperative situations by proposing a signal acquisition method based on multi-device collaboration and statistical analysis to solve problems such as high acquisition probability, high estimation accuracy, and low computational complexity.

[0005] The technical solution adopted in this invention is as follows:

[0006] A signal acquisition method based on multi-device collaboration and statistical analysis includes the following steps:

[0007] Step 1: Synchronously acquire the target frequency signal using signal acquisition equipment. Each target frequency signal is sampled at multiple sampling points, i.e. , , The number of target frequency signals to be collected. Sampling points for each target frequency signal;

[0008] Step 2: Calculate the signal amplitude of each target frequency signal using the autocorrelation algorithm. The target frequency signal with the largest signal amplitude is used as the reference signal. ;

[0009] Step 3: Calculate the correlation peaks between each target frequency signal and the reference signal using a cross-correlation algorithm. And calculate the relevant statistics for each peak, including the second peak. and the mean of related peaks The second peak value is the second largest peak value after normalization of the relevant peaks.

[0010] Step 4: Set thresholds for the second relevant peak and mean. and If there is Each target frequency signal satisfies the threshold condition, i.e. and If the signal is captured, then it is considered that a signal has been captured; where, This is the set value.

[0011] Furthermore, in step one, the signal acquisition device is one or more... When there is only one signal acquisition device, the device monitors and acquires signals in a 360° azimuth. A target frequency signal, the signal acquisition device is... At any given time, each signal acquisition device acquires one target frequency signal.

[0012] Furthermore, in step two, the signal amplitude is calculated as follows:

[0013]

[0014]

[0015] In the formula, It is a constant, calibrated based on the link gain, bandwidth, and number of sampling points of the signal acquisition equipment. and For Fast Fourier Transform and its inverse transform, It is a conjugate function. It is an L2 norm.

[0016] The advantages of this invention compared to the prior art are:

[0017] This invention overcomes the limitations of existing methods that require tiered threshold settings for signal acquisition. This method can distinguish between target and noise signals with a single threshold setting, improving computational efficiency and acquisition accuracy. Furthermore, it maintains excellent performance in signal amplitude calculation and signal acquisition even under low signal-to-noise ratio (SNR) and certain negative SNR conditions. Detailed Implementation

[0018] The present invention will be described in detail below through specific implementation examples.

[0019] This invention is a signal acquisition method based on multi-device collaboration and statistical analysis, and its execution process is as follows:

[0020] Step 1: First, use signal acquisition equipment to synchronously acquire the target frequency signal. The receiving antenna is a directional antenna, and the data type is IQ data, denoted as... ;Signal acquisition for each target frequency Each sampling point, i.e. .

[0021] This invention is mainly applied to multiple single-channel signal acquisition devices, each acquiring one target frequency signal; it is equivalent to applying a single multi-channel signal acquisition device to monitor signals in a 360° azimuth. A target frequency signal.

[0022] Step 2: Calculate the signal amplitude of each target frequency signal using the autocorrelation algorithm. ,in,

[0023]

[0024]

[0025] In the formula, This is a constant and can be calibrated based on the link gain, bandwidth, and number of sampling points of the signal acquisition equipment. and For Fast Fourier Transform and its inverse transform, It is a conjugate function. The L2 norm is used. The target frequency signal with the largest amplitude is selected as the reference signal, denoted as . .

[0026] Step 3: Using the cross-correlation algorithm, find the normalized correlation peaks between each target frequency signal and the reference signal. ,in , ;

[0027] Two statistics related to the correlation peaks are used here: the second correlation peak and the average value, which are defined as follows:

[0028] 1) Second correlation peak The highest peak value within the range of the left and right boundaries is obtained by searching the left and right boundaries monotonically from the highest peak value until the minimum value is reached.

[0029] 2) Average value ;

[0030] Based on the test results, in order to balance multipath and complex signal conditions, thresholds are set for the second correlation peak and mean, specifically as follows:

[0031] 1)

[0032] 2) .

[0033] In scenarios involving multi-device positioning, if When the correlation peaks of all target frequency signals meet the threshold requirements, it indicates that the signal has been captured. The settings can be adjusted based on factors such as the number of signal acquisition devices and the signal reception distance of each device. In the actual test, there were 4 signal acquisition devices. Due to factors such as urban building obstruction and reception distance limitations, the k value was set to 3. Related statistics for the peaks can also include standard deviation, kurtosis, and skewness.

[0034] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A signal acquisition method based on multi-device cooperation and statistical quantity analysis, characterized in that, The method comprises the following steps: Step one: synchronously collect target frequency signals by using a signal collection device , wherein a plurality of sampling points are collected for each target frequency signal, i.e. , , is the number of collected target frequency signals, is the sampling point of each target frequency signal; Step two: calculate the signal amplitude of each target frequency signal by using autocorrelation algorithm , and take the target frequency signal with the largest signal amplitude as the reference signal ; Step three: calculate the correlation peak between each target frequency signal and the reference signal by using the cross-correlation algorithm , and calculate the relevant statistics of the correlation peak respectively, including the second peak value and the correlation peak mean value ; wherein the second peak value is the second largest peak value after normalization of the correlation peak; Step four: setting threshold values for the second correlation peak and mean value and if there are target frequency signals that satisfy the threshold condition, i.e. and then the signal is considered to be captured; wherein is a set value.

2. The signal acquisition method based on multi-device cooperation and statistical analysis according to claim 1, characterized in that, In step one, the signal acquisition device is one or more. When the signal acquisition device is one, the signal acquisition device monitors signals in 360° azimuth and acquires one target frequency signal. When the signal acquisition device is more than one, each signal acquisition device acquires one target frequency signal. more. When the signal acquisition device is one, the signal acquisition device monitors signals in 360° azimuth and acquires one target frequency signal. When the signal acquisition device is more than one, each signal acquisition device acquires one target frequency signal.​ 3. The signal acquisition method based on multi-device cooperation and statistical analysis according to claim 1, characterized in that, In step two, the signal amplitude is calculated in the following way: In the formula, is a constant, calibrated according to the link gain, bandwidth and sampling point number of the signal acquisition device, and is a fast Fourier transform and inverse transform, is a conjugate function, is an L2 norm.

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