5G external radiation source radar detection method based on SSB signal

Abstract

The present invention discloses a 5G external radiation source radar detection method based on SSB signals, which belongs to the technical field of external radiation source radar. External radiation source radar is a device that uses non-cooperative radiation source signals to detect targets. It can detect various types and batches of low-altitude targets in a radio silent manner, and has the advantages of low cost, no radiation, and strong networking detection capabilities. However, in complex environments such as cities, 5G base stations are densely deployed, and multiple base station signals with the same frequency overlap and interfere with each other. To address the problem of same-frequency aliasing, it is proposed to adopt a purification method based on "demodulation + modulation" to reconstruct the reference signal, detect and reconstruct the SSB beam of the detection base station, and use it as a radar pulse signal for target detection, so as to achieve accurate detection of low-altitude targets.

Description

Technical Field

[0001] The present invention belongs to the technical field of external radiation source radar target detection, and in particular to a 5G external radiation source radar detection method based on SSB signals. Background Art

[0002] In recent years, the low-altitude economy has flourished, but this has been accompanied by an endless stream of "illegal" drones causing flight disruptions, injuries, and other incidents, which have had a huge impact on social stability.

[0003] An external radiation source radar is a device that uses non-cooperative radiation source signals to detect targets. It does not emit signals itself, but detects by receiving echo signals from non-cooperative radiation sources (radio, television, communication base stations, etc.) reflected by the target. It can detect various types and batches of low-altitude targets in a radio silent manner. It has the advantages of low cost, no radiation, and strong networking detection capabilities. It is particularly suitable for urban environments that have restrictions on electromagnetic radiation and high requirements for detection performance.

[0004] However, in complex environments such as cities, 5G base stations are densely deployed, and in order to save spectrum resources, different 5G transmitting base stations share the same frequency band. The signals of multiple base stations with the same frequency overlap and interfere with each other. In such a scenario, the external radiation source radar receiving channel will not only receive the direct wave signal and target echo signal that are useful for target detection, but also alias the radiation source signals of each base station with the same frequency. Due to the influence of the same frequency aliasing signal, the target detection performance of the external radiation source radar system is reduced, and multiple false targets may be generated.

[0005] Compared with the prior art, the differences are as follows:

[0006] Technical comparison with patent CN116660856B "A method for processing external radiation source radar signals based on 5G time slot synchronization";

[0007] 1. Patent CN116660856B mainly targets the interference problem of uplink time slots and downlink time slots on radar detection in 5G time division duplex (TDD) mode. This method searches and decodes SSB signals to achieve time-frequency synchronization of 5G signal frames and removes uplink time slot interference, thereby improving the resolution and signal-to-noise ratio of target detection. The present invention focuses on solving the problem of co-frequency interference of 5G base stations, reconstructing the reference signal through "demodulation + modulation", detecting and reconstructing the SSB beam, and using the SSB signal as a radar pulse signal to achieve accurate detection of targets in complex urban environments, avoiding interference caused by the aliasing of multiple co-frequency base station signals.

[0008] Second, in terms of processing methods, patent CN116660856B emphasizes time slot management. By identifying and removing uplink time slots, it avoids the negative impact of uplink signals on range-Doppler processing and optimizes the delay of target detection and Doppler frequency shift information extraction. The present invention focuses on signal purification and reconstruction in processing methods. By detecting and processing co-frequency interference signals, it ensures accurate detection of targets even in the case of signal aliasing.

[0009] 3. Patent CN116660856B focuses on time slot synchronization and elimination of uplink time slot influence to achieve accurate time-frequency synchronization. The present invention focuses more on improving signal quality, improving signal purity through cell search, channel estimation and reconstruction, clutter suppression and other steps, thereby improving detection performance.

[0010] Fourth, in terms of technical applicability, patent CN116660856B mainly deals with target detection in 5G TDD transmission mode, emphasizing processing optimization in the time domain to reduce interference in time slot arrangement. The present invention is more effective in dealing with urban environments with dense co-channel interference, ensuring that targets can still be accurately identified in complex signal environments.

[0011] Technical comparison with patent CN108398676B "A method for detecting weak moving targets with external radiation source radar";

[0012] 1. Patent CN108398676B focuses on solving the problem of detecting weak moving targets, especially target identification in a low signal-to-noise ratio environment, while the present invention is aimed at the impact of multi-base station signal aliasing on the detection performance of external radiation source radar in a 5G network environment, especially in complex urban scenes.

[0013] 2. Patent CN108398676B adopts the strategy of frequency domain coherent accumulation and delay change rate search, focusing on the optimization of signal processing and matching; while the present invention introduces reconstruction technology based on SSB signals, purifies the signal through demodulation and modulation processing, combats co-channel interference, and emphasizes the adaptability and anti-interference ability in the 5G signal environment.

[0014] 3. Patent CN108398676B realizes signal matching and energy focusing through frequency shift matrix and phase compensation. The present invention applies steps such as cell search, channel estimation and reconstruction to improve signal purity, as well as signal processing in fast and slow time dimensions to achieve accurate detection of the target. Summary of the invention

[0015] The technical problem to be solved by the present invention is to provide a 5G external radiation source radar detection method based on SSB signals. In order to solve the problem of co-frequency aliasing, a purification method based on "demodulation + modulation" reconstruction of reference signals is proposed to detect and reconstruct the SSB beam of the detection base station as a radar pulse signal for target detection, so as to achieve accurate detection of low-altitude targets.

[0016] To achieve the above object, the present invention provides a 5G external radiation source radar detection method based on SSB signal, comprising the following method steps:

[0017] Step S1, receiving the 5G multi-base station aliasing signal in the reference channel of the external radiation source radar, performing cell search on the received signal, finding the strongest cell, then performing channel estimation and reconstruction, eliminating the interference of the strongest cell, and then using the same method to search for the next cell until all cells are detected, thereby realizing the cell information analysis of all base stations with the same frequency;

[0018] Step S2: Combine the prior information of the external radiation source radar detection base station, distinguish the co-frequency interference base station of the detection base station, synthesize the SSB signal according to the cell ID number of the detection base station, PBCH payload content and other information, and obtain the purified reconstructed signal through OFDM modulation. Simultaneously record the time offset and frequency offset between the reconstructed signal and the received signal;

[0019] Step S3, echo channel adjustment;

[0020] Step S3 specifically includes:

[0021] After phase alignment and frequency offset adjustment of the monitoring channel signal, it is defined as: n=0,1,…,N-1;

[0022] where τ n is the time offset between the reconstructed signal of the reference channel and the received signal, f ε is the carrier frequency deviation;

[0023] Step S4: Suppress clutter in the echo channel and extract the echo signal containing target information

[0024] Step S5, range-Doppler processing;

[0025] Step S6: target detection.

[0026] Furthermore, step S5 specifically includes:

[0027] (5.1) Define the total coherent accumulation time as T int , with SSB transmission period T SSBSegment the reconstructed signal and the echo signal for the pulse repetition period and construct a fast and slow time matrix;

[0028] (5.2) performing cross-correlation processing on the corresponding reconstructed signal and the echo signal in the fast time dimension;

[0029] (5.3) Perform Fourier transform along the slow time dimension to obtain the range-Doppler spectrum, which is defined as:

[0030]

[0031] Among them: The number of samples in each segment of the fast time dimension is defined as N b , the duration is the SSB transmission period T SSB ; The total number of segments in the slow time dimension is defined as M, that is, T int / T SSB ;

[0032] The measurement range of the target distance is defined as:

[0033] R∈[0,N b -1]*τ

[0034] The measurement range of Doppler frequency is defined as:

[0035]

[0036] The measurement range corresponding to the target bistatic velocity is defined as:

[0037]

[0038] Furthermore, step S6 specifically includes:

[0039] (6.1) After detecting the target, the target speed is defined as:

[0040]

[0041] Where i is the number of measurements, N is the number of times the velocity is aliased, and V max represents the target velocity range measured in the range-Doppler spectrum and is defined as:

[0042]

[0043] (6.2) When the target moves at a constant speed, the velocity measurement results of the two range-Doppler spectra are defined as:

[0044]

[0045] Define Δt = t2-t1, then the target distance change during this period is defined as:

[0046]

[0047] (6.3) The number of times velocity aliasing occurs;

[0048]

[0049] Substitute the result calculated from the above formula (5.15);

[0050]

[0051] The actual measured speed of the target can be obtained.

[0052] Beneficial effects: The 5G external radiation source radar detection technology based on SSB signal provided by the present invention adopts a purification method based on "demodulation + modulation" to reconstruct the reference signal, detects and reconstructs the SSB beam of the detection base station, and uses it as a radar pulse signal for target detection, distinguishes the detection base station from the same-frequency interference base station, and improves the signal-to-noise ratio. After matching filtering using the distance correlation-Doppler transform method, the dual-base distance of the target is accurately obtained through distance-Doppler processing, and then the fuzzy speed of the target is estimated using the range-Doppler spectrum measured multiple times, so as to achieve effective detection of the target. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of a 5G external radiation source radar detection technology based on SSB signal of the present invention;

[0054] Figure 2 is a low-altitude detection scene diagram under a complex environment in an embodiment of the present invention;

[0055] Figure 3 It is a diagram of fuzzy estimation of target speed of unmanned aerial vehicle in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. It should be noted that the words "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to directions in the accompanying drawings, and the words "inner" and "outer" refer to directions toward or away from the geometric center of a specific component, respectively.

[0057] The present invention provides a 5G external radiation source radar detection method based on SSB signal, which adopts a purification method based on "demodulation + modulation" to reconstruct the reference signal, detects and reconstructs the SSB beam of the detection base station, and uses it as a radar pulse signal for target detection, distinguishes the detection base station from the same-frequency interference base station, and improves the signal-to-noise ratio. After matching filtering using the range correlation-Doppler transform method, the dual-base distance of the target is accurately obtained through range-Doppler processing, and the fuzzy speed of the target is estimated using the range-Doppler spectrum measured multiple times, so as to achieve effective detection of the target.

[0058] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments. As a specific embodiment of the present invention, the present invention provides a 5G external radiation source radar detection method based on SSB signals, and the flow chart is as follows: Figure 1 As shown in Figure 2, the low-altitude detection scene in a complex environment is as follows: Figure 2 , the specific steps are as follows:

[0059] Step S1: Receive 5G multi-base station aliasing signals in the reference channel of the external radiation source radar, and perform cross-correlation and physical broadcast channel decoding on the aliasing signals received by the reference channel according to the three primary synchronization sequences PSS and 336 secondary synchronization sequences SSS defined in the 5G NR standard protocol, and perform cell search on the received signal to find the strongest cell. Perform channel estimation and reconstruction to eliminate the interference of the strongest cell, and then use the same method to search for the next cell until all cells are detected, so as to realize the cell information analysis of all base stations with the same frequency;

[0060] Step S2: Combine the prior information of the external radiation source radar detection base station to distinguish the co-frequency interference base station of the detection base station. Synthesize the SSB signal according to the cell ID number of the detection base station, PBCH payload content and other information, and obtain the purified reconstructed signal through OFDM modulation. Simultaneously record the time offset and frequency offset between the reconstructed signal and the received signal;

[0061] Step S3, after phase alignment and frequency offset adjustment of the monitoring channel signal, is defined as: n=0,1,…,N-1

[0062] where τ n is the time offset between the reconstructed signal of the reference channel and the received signal, f ε is the carrier frequency deviation.

[0063] Step S4: Suppress clutter in the echo channel and extract the echo signal containing target information

[0064] Step S5: define the total coherent accumulation time as T int, with SSB transmission period T SSB The reconstructed signal and echo signal are segmented for the pulse repetition period, and the fast and slow time matrices are constructed. The corresponding reconstructed signal and echo signal are cross-correlated in the fast time dimension. Fourier transform is performed along the slow time dimension to obtain the range-Doppler spectrum, which is defined as:

[0065]

[0066] Among them: The number of samples in each segment of the fast time dimension is defined as N b , the duration is the SSB transmission period T SSB ; The total number of segments in the slow time dimension is defined as M, that is, T int / T SSB .

[0067] The measurement range of the target distance is defined as:

[0068] R∈[0,N b -1]*τ

[0069] The measurement range of Doppler frequency is defined as:

[0070]

[0071] The measurement range corresponding to the target bistatic velocity is defined as:

[0072]

[0073] Step S6: After the target is detected, the target speed is defined as:

[0074]

[0075] Where i is the number of measurements, N is the number of times the velocity is aliased, and V max represents the target velocity range measured in the range-Doppler spectrum and is defined as:

[0076]

[0077] When the target moves at a constant speed, the velocity measurement results of the two range-Doppler spectra can be defined as:

[0078]

[0079] Define Δt = t2-t1, then the target distance change during this period is defined as:

[0080]

[0081] The number of times velocity aliasing occurs:

[0082]

[0083] Substitute the result calculated from the above formula (5.15) into

[0084]

[0085] The actual measured speed of the target can be obtained.

[0086] Figure 3 This is a diagram of the fuzzy estimation of the target speed of the drone. In this embodiment, the flight speed of the drone is 3m / s, the carrier center frequency of the 5G signal is 2.545GHz, and the transmission period of the SSB signal is 20ms, so the measurement range of the target dual-base speed in the range-Doppler spectrum is -1.47m / s to 1.47m / s. Substituting the target speed measurement range and the measured dual-base speed, it can be inferred that the measured target true speed is about -2.77m / s. Due to the limitations of distance resolution and speed resolution, there is a slight error between the measured speed and the true speed recorded by the drone, but it is basically close to the true value.

[0087] The experimental results show that the 5G external radiation source radar target detection method based on SSB signal can realize accurate detection of UAV targets, which verifies the feasibility and effectiveness of the method of the present invention.

[0088] It should be noted that the above content only illustrates the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. For ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications all fall within the protection scope of the claims of the present invention.

Claims

1. A 5G external radiation source radar detection method based on SSB signal, characterized in that: The method comprises the following steps: Step S1, receiving the 5G multi-base station aliasing signal in the reference channel of the external radiation source radar, performing cell search on the received signal, finding the strongest cell, then performing channel estimation and reconstruction, eliminating the interference of the strongest cell, and then using the same method to search for the next cell until all cells are detected, thereby realizing the cell information analysis of all base stations with the same frequency; Step S2: Combine the prior information of the external radiation source radar detection base station, distinguish the co-frequency interference base station of the detection base station, synthesize the SSB signal according to the cell ID number and PBCH payload content information of the detection base station, and obtain the purified reconstructed signal through OFDM modulation. Simultaneously record the time offset and frequency offset between the reconstructed signal and the received signal; Step S3, echo channel adjustment; After phase alignment and frequency offset adjustment of the monitoring channel signal, it is defined as: where τ n is the time offset between the reconstructed signal of the reference channel and the received signal, f ε is the carrier frequency deviation; Step S4: Suppress clutter in the echo channel and extract the echo signal containing target information Step S5, range-Doppler processing; (5.1) Define the total coherent accumulation time as T int , with SSB transmission period T SSB Segment the reconstructed signal and the echo signal for the pulse repetition period and construct a fast and slow time matrix; (5.2) performing cross-correlation processing on the corresponding reconstructed signal and the echo signal in the fast time dimension; (5.3) Perform Fourier transform along the slow time dimension to obtain the range-Doppler spectrum, which is defined as: Among them: The number of samples in each segment of the fast time dimension is defined as N b , the duration is the SSB transmission period T SSB ; The total number of segments in the slow time dimension is defined as M, that is, T int / T SSB ; The measurement range of the target distance is defined as: R∈[0,N b -1]*t The measurement range of Doppler frequency is defined as: Step S6: target detection; (6.1) After detecting the target, the target speed is defined as: Where i is the number of measurements, K is the number of times the velocity is aliased, and V max represents the target velocity range measured in the range-Doppler spectrum and is defined as: (6.2) When the target moves at a constant speed, the velocity measurement results of the two range-Doppler spectra are defined as: Define Δt = t2-t1, then the target distance change during this period is defined as: (6.3) The number of times velocity aliasing occurs; Substitute the result calculated by the above formula into; The actual measured speed of the target can be obtained.

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