A recording device detection method and system based on electromagnetic signals

Abstract

This invention discloses a method for detecting recording devices based on electromagnetic signals, comprising the following steps: acquiring radio frequency signals in the environment; performing spectrum analysis on the radio frequency signals after filtering, denoising, and smoothing; searching for peak points belonging to the frequency band of the electromagnetic radiation signal of the recording device in the spectrum, and calculating the average peak interval; matching the peak interval with the frequency feature library of the recording device's AD conversion drive signal, and confirming the detection of the recording device if they are equal. This invention can detect unknown and concealed recording devices by utilizing the electromagnetic radiation signals generated by the AD conversion of the recording device during normal operation, and can locate the device by multiple detections from different directions. It is suitable for private occasions such as confidential meetings and private conversations, with an effective distance of 20 centimeters.

Description

Technical Field

[0001] This invention belongs to the field of equipment testing, specifically relating to a method and system for testing recording equipment based on electromagnetic signals. Background Technology

[0002] With societal development, people are increasingly valuing the protection of privacy and security. In confidential meetings and private conversations, it's crucial to ensure participants are not carrying recording devices intended for privacy theft. However, recording devices like voice recorders, due to their small size and ability to be concealed, are often difficult for others to detect, making them one of the most common tools for privacy theft. Therefore, feasible and practical technical methods for detecting recording devices are particularly important. Existing device detection technologies, such as radio frequency detectors, metal scanners, and flow detectors, are not applicable to recording devices: because voice recorders typically record offline and store locally, they do not actively emit signals, rendering radio frequency detectors and flow detectors unsuitable; and metal scanners cannot distinguish between different devices or metal objects, thus being inapplicable in certain situations. In conclusion, there is currently no feasible technical method for detecting recording devices. Summary of the Invention

[0003] This invention discloses a method for detecting recording devices based on electromagnetic signals. This method utilizes the electromagnetic signals generated by the A / D conversion of the recording device during normal operation to detect unknown or concealed recording devices. The signal receiving device is compact and easy to install on the underside or side of a conference table, making it suitable for confidential meetings, private conversations, and other private occasions. The effective detection distance is 20 centimeters.

[0004] To achieve the above objectives, according to a specific embodiment of the present invention, the method for detecting recording devices based on electromagnetic signals includes the following steps:

[0005] Step 1: Use an RF signal receiving device to collect RF signals in the environment to be tested. The operating frequency band of the device must meet the frequency range of the electromagnetic radiation signal generated by the AD conversion of the recording device, which is usually 20–150 MHz.

[0006] Step 2: Analyze the acquired radio frequency signal using signal processing software. First, perform Fast Fourier Transform (FFT) to generate the original spectrum. Then, after smoothing, generate the denoised spectrum. Finally, use a peak detection algorithm to determine whether there are equally spaced peaks in the spectrum and calculate the frequency interval between the equally spaced peaks.

[0007] Step 3: Match the calculated interval frequency with the frequency feature library of the recording device's AD conversion drive signal. If the data matches, it indicates that the recording device has been detected in the surrounding environment.

[0008] In the above technical solution, a radio frequency signal receiving device is used to collect radio frequency signals in the environment to be tested, and the operating frequency band of the device should cover 20–150 MHz.

[0009] Furthermore, the acquired radio frequency signal is processed as follows: first, a Fast Fourier Transform (FFT) is performed to generate the original spectrum, then a denoised spectrum is generated after smoothing, and finally, it is determined whether there are equally spaced peak points in the spectrum. If so, the interval frequency is calculated.

[0010] Furthermore, the criterion for determining whether peaks are equally spaced is to calculate the interval Δf between all peak frequencies. i Whether the ratio μ of variance to mean is less than the threshold is calculated using the following formula:

[0011]

[0012] Where i is the i-th interval, D(Δf) i E(Δf) represents the variance of the interval between all adjacent peaks. i The value is the average of the intervals between all adjacent peaks. A threshold of 0.01 is typically used. If the value is less than the threshold, then equally spaced peaks exist, with an interval frequency of E(Δf). i ).

[0013] Furthermore, the processing of the acquired radio frequency signals can be directly implemented using Matlab.

[0014] Furthermore, the frequency feature library of the recording device's AD conversion drive signal includes the recording device's chip model and its corresponding AD conversion drive signal frequency.

[0015] Furthermore, if the peak interval frequency is equal to or deviates from a frequency in the frequency feature library of the AD conversion drive signal of the recording device within ±5%, it is considered to be consistent.

[0016] The present invention also provides a recording device detection system based on electromagnetic signals, comprising:

[0017] A signal receiving device used to collect radio frequency signals in the environment, with an operating frequency band covering 20–150 MHz;

[0018] The signal analysis module is used to perform fast Fourier transform on the signal collected by the signal receiving device, obtain the original electromagnetic signal spectrum, and then perform smoothing processing, mark the peaks in the spectrum, determine whether there are equally spaced peak points, and calculate the frequency of equally spaced peak intervals.

[0019] The feature library matching module is used to compare the peak interval frequency obtained by the signal analysis module with the pre-built frequency feature library of the recording device's AD conversion drive signal.

[0020] The beneficial effects of this invention are:

[0021] The signal collected by this invention is the electromagnetic radiation signal generated by the drive signal of the AD conversion during the recording process of the recording device. This signal belongs to the energy leaked by the recording device itself when it is working normally. Therefore, it overcomes the prerequisite of existing technologies such as flow detectors that require the device to transmit signals to the outside world. It can not only detect online recording devices that transmit audio files in real time, but also detect offline recording devices that record and save locally without actively emitting signals. Therefore, it is more suitable for detecting unknown and hidden recording devices.

[0022] This invention matches the interval frequency obtained from signal processing and analysis with the frequency feature library of the AD conversion drive signal of the recording device, thereby enabling targeted determination of whether the signal is generated by the recording device. This overcomes the problem that existing technologies such as metal scanners cannot distinguish the type of electronic device detected, resulting in a lower false detection rate. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained from these drawings without creative effort.

[0024] Figure 1 This is a structural block diagram of the recording device detection method based on electromagnetic signals according to the present invention.

[0025] Figure 2 This is a schematic diagram of the connections between the various devices in the signal receiving and processing apparatus of the present invention, along with corresponding physical images.

[0026] Figure 3 This is the original spectrum diagram of the electromagnetic radiation signal collected from the recording device.

[0027] Figure 4 The denoised spectrum of the electromagnetic radiation signal from the recording device.

[0028] Figure 5 A schematic diagram of equally spaced peak points marked for the peak detection algorithm. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0030] This application will use terminology commonly employed by those skilled in the art to describe various aspects of the illustrative embodiments in order to convey the essence of their work to others skilled in the art. However, it will be apparent to those skilled in the art that alternative embodiments can be practiced using portions of the described aspects. For purposes of explanation, specific figures, materials, and configurations are set forth to provide a thorough understanding of the illustrative embodiments. However, it will be apparent to those skilled in the art that alternative embodiments can be implemented without specific details. In other instances, some well-known features have been omitted or simplified in order not to obscure the illustrative embodiments.

[0031] The recording device detection method based on electromagnetic signals of this invention includes steps such as raw radio frequency signal acquisition, signal processing algorithm, peak interval calculation, and peak frequency matching. The detection logic is as follows: Figure 1 As shown.

[0032] In this embodiment, the signal receiving device consists of a receiving antenna, a low-noise signal amplifier, and software radio. The signal receiving device is configured according to... Figure 2 The structure shown is connected and, during operation, collects radio frequency signals from the environment and transmits them to a host computer running signal analysis software. The selected equipment must cover the frequency range of electromagnetic radiation signals generated by the AD conversion of the recording equipment, typically 20–150 MHz. In this example, the rubber rod antenna operates in the 20–512 MHz band, the low-noise amplifier LNA-250 operates in the 10–250 MHz band, and the software-defined radio USRP N210 operates in the 10–6000 MHz band, all meeting the above requirements. This example uses a Lenovo laptop running MATLAB signal processing software. It should be noted that the above hardware, equipment, and software are only one feasible embodiment and can be replaced with any other model of equipment that meets the frequency requirements.

[0033] In MATLAB signal processing software, the signal file is first subjected to a Fast Fourier Transform to obtain the original spectrum of the electromagnetic signal in the environment, such as... Figure 3 As shown, the waveform exhibits equally spaced peaks and glitches. The signal strength of approximately -80 dBm represents the ambient noise level in this example, while the peaks indicate the presence of signal components at those frequencies. The Fast Fourier Transform (FFT) can be performed using the built-in FFT algorithm in MATLAB software.

[0034] Secondly, a smoothing algorithm is used to remove glitches from the spectrum, making the signal components more prominent and facilitating peak detection. Figure 4 for Figure 3The electromagnetic signal spectrum after denoising. The denoising process can be completed using the smoothdata algorithm built into MATLAB software.

[0035] Next, each peak in the spectrum is labeled using a peak detection algorithm, such as... Figure 5 As shown in the figure, each detected peak is marked, and the numerical value represents the frequency corresponding to the peak point. The algorithm will automatically mark each peak and then calculate the interval Δf between each adjacent peak. i Determine whether the peaks are evenly spaced; if so, calculate the average peak interval E(Δf). i Otherwise, it is assumed that no recording device exists. The peak detection algorithm can be implemented using the findpeaks algorithm in MATLAB software. This requires setting the minimum interval distance MinD based on the number of signal sampling points S and the sampling bandwidth F. The calculation formula is:

[0036]

[0037] In this example, the number of sampling points S is 200,000, and the sampling bandwidth is 100,000,000 Hz. Therefore, the minimum interval distance MinD is 500. The criterion for determining whether the peaks are equally spaced is to calculate all intervals Δf. i Whether the ratio μ of variance to mean is less than a certain threshold is determined by the following formula:

[0038]

[0039] Where D(Δf) i E(Δf) represents the variance of the interval between all adjacent peaks. i The average interval E(Δf) is the average of all adjacent peak intervals, typically with a threshold of 0.01. In this example, the average interval E(Δf) is... i The frequency is 3.2534 MHz.

[0040] Finally, this interval value is matched with the frequency feature library of the recording device's AD conversion drive signal (Table 1). It can be seen that the average interval is close to the feature value of serial number 3, indicating that the recording device's presence has been detected in the surrounding environment. Table 1 records the AD conversion drive signal frequencies of different brands and models of recording devices. This table will add feature values ​​as new products and chips are applied. It should be noted that due to factors such as measurement errors in the receiving device and design errors in the recording device chip, the measured average peak interval may not be completely consistent with the value in the feature library; the allowable error is within ±5%.

[0041] Table 1. Frequency Feature Library of AD Conversion Drive Signals for Recording Equipment

[0042] Serial Number Chip Model AD conversion drive signal frequency (MHz) 1 RTL 8722CS 5.00 2 ATJ 2127 24.00 3 MT 2523S 3.25 4 WS 200 12.00 5 ATJ 3315D-X 24.00 6 JL AC6901 6.00 7 AK 2115C 24.00 8 ATS 2837 24.00

Claims

1. A method for detecting recording devices based on electromagnetic signals, characterized in that, Including the following: The radio frequency signal receiving device is used to collect radio frequency signals in the environment. The operating frequency band of the device should cover 20-150 MHz. The radio frequency signal is first subjected to a Fast Fourier Transform (FFT) to generate an original spectrum, and then smoothed to generate a denoised spectrum. The peak points belonging to the frequency band of the electromagnetic radiation signal of the recording device are searched in the spectrum to determine whether there are equally spaced peak points and to determine the interval frequency of the equally spaced peak points. The standard for determining whether the peak points are equally spaced is whether the ratio of the variance to the mean of the intervals of all peak frequencies is less than a threshold. If it is less than the threshold, then equally spaced peak points exist. The interval frequency is the average value of the intervals of all adjacent peaks. The peak interval frequency is matched with the frequency feature library of the recording device's AD conversion drive signal. If a matching frequency is found, the recording device is confirmed to have been detected. The frequency feature library of the recording device's AD conversion drive signal includes the recording device's chip model and its corresponding AD conversion drive signal frequency. When the peak interval frequency is equal to or deviates from a frequency in the frequency feature library of the recording device's AD conversion drive signal, it is judged to be consistent.

2. The method for detecting recording devices based on electromagnetic signals according to claim 1, characterized in that, The threshold is set to 0.

01.

3. The method for detecting recording devices based on electromagnetic signals according to claim 1, characterized in that, The processing of the acquired radio frequency signals can be directly implemented using Matlab.

4. A recording device detection system based on electromagnetic signals, characterized in that, For implementing the method as described in any one of claims 1-3, comprising: A signal receiving device used to collect radio frequency signals in the environment, with an operating frequency band covering 20–150 MHz; The signal analysis module is used to perform fast Fourier transform on the signal collected by the signal receiving device, obtain the original electromagnetic signal spectrum, and then perform smoothing processing, mark the peaks in the spectrum, determine whether there are equally spaced peak points, and calculate the frequency of equally spaced peak intervals. The feature library matching module is used to compare the peak interval frequency obtained by the signal analysis module with the pre-built frequency feature library of the recording device's AD conversion drive signal.

Images