Navigation anti-interference method based on electric field polarization phase quadrature

Abstract

The application relates to the technical field of satellite navigation, and particularly discloses a navigation anti-interference method based on electric field polarization phase orthogonality, which comprises the following steps: obtaining a first gain signal by regulating and controlling a gain factor; linearly superimposing the first gain signal and a second signal to obtain a double-frequency signal; simulating according to the double-frequency signal to obtain a mixed spectrum image; determining a critical value when a characteristic peak value of the second signal is submerged; setting the first signal and the second signal to propagate along a z-axis to obtain first signal electric field intensity and second signal electric field intensity; generating first signal electric field and second signal electric field; horizontally polarizing the first signal electric field and vertically polarizing the second signal electric field; visually displaying the double-frequency signal reaching a mixed boundary condition to show orthogonal polarization propagation characteristics; and performing navigation anti-interference according to the critical value and the orthogonal polarization propagation characteristics. The application realizes signal space domain isolation at a radiation source head and suppresses mutual interference type navigation denial.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation technology, and specifically to a navigation anti-interference method based on orthogonal electric field polarization phase. Background Technology

[0002] Global navigation satellite systems face severe spectrum congestion, exacerbating the risk of navigation denial due to spectrum leakage. In the BeiDou B1I / B1C bands, when the B1C signal power increases, its second harmonic component overlaps with the B1I main lobe signal, causing B1I navigation messages to become unreadable and creating a typical navigation denial scenario.

[0003] Currently, there are various methods to solve the problem of spectrum leakage, including slow truncation (windowing) techniques, interpolation techniques, adaptive sampling rate algorithms, iterative methods, and signal orthogonal transformation.

[0004] The slow truncation technique reduces spectral leakage by using a slowly changing window function instead of the abrupt truncation of a rectangular window when truncating the signal. Its advantages include reduced spectral leakage and improved spectral analysis accuracy. However, the addition of the window function alters the waveform of the original signal, potentially leading to signal distortion and increased computational complexity. During Fast Fourier Transform (FFT), signal truncation causes spectral leakage. To mitigate this effect, Cui Can et al., based on window function theory, used Matlab to plot the time and frequency domain amplitude response curves of Hanning, Hamming, rectangular, triangular, and Blackman windows. By analyzing the mechanism of spectral leakage and comparing the characteristics and performance of each window function, they explored how to effectively suppress the impact of spectral leakage on signal analysis accuracy through optimal window function selection in signal truncation processing. Li Xianru and Yang Lizhang found that traditional Orthogonal Frequency Division Multiplexing (OFDM) is at a disadvantage in 5G communication due to high out-of-band leakage. They explored methods to improve the above problems, such as using filtered OFDM (F-OFDM) with various window functions for soft truncation and combining it with Nuttall's Blackman-Harris window.

[0005] Interpolation techniques improve spectral leakage by adding data points or employing specific interpolation algorithms. Their advantages include better approximation of the original signal, reduced spectral leakage impact, strong adaptability, and good flexibility. However, because interpolation requires additional processing of the sampled data, it suffers from drawbacks such as large data volume, long processing cycle, poor real-time performance, and the introduction of errors. To reduce the impact of spectral leakage and improve the accuracy of power grid harmonic and interharmonic detection, Zhao Shuaiqi et al. proposed a combined analysis method based on multi-spectral line interpolation and complex modulation refinement, which has been verified to obtain accurate signal parameters.

[0006] Adaptive sampling rate algorithms are based on real-time adjustment of the sampling frequency to keep it synchronized with the signal frequency, avoiding spectral leakage caused by asynchrony between the sampling and signal frequencies. Their advantages include improved measurement accuracy and strong adaptability, while disadvantages include high algorithm complexity, potential introduction of phase errors, and significant real-time challenges. To eliminate spectral leakage and the picket fence effect during fundamental frequency extraction, Wang Yinglong et al. introduced a fundamental frequency extraction algorithm based on adaptive frequency tracking, significantly improving the accuracy of fundamental component extraction. Niu Zhong addressed the interference problem in measurement and control communication systems by implementing FPGA adaptive threshold methods and space-time adaptive algorithms in the frequency and space-time domains, respectively, verifying the practicality of the two adaptive algorithms. Zhang Chuang et al. addressed the issue that slowly varying faults in subsystems affect the accuracy of federated filters by using adaptive filtering to adaptively adjust the measurement noise array, reducing the impact of slowly varying faults on global accuracy and improving system reconfiguration capabilities.

[0007] Orthogonal signal transform (ORT) is a signal processing technique based on the orthogonal characteristics of signals. Its properties enable multiplexing, improving spectral efficiency and reducing spectral leakage. First, because orthogonal signals have non-overlapping spectral characteristics in the frequency domain, processing them can reduce interference between signals and improve processing accuracy. Second, by decomposing the signal to be processed into orthogonal components, each component can be processed and analyzed independently, thus improving processing efficiency. Finally, orthogonal signal processing methods are robust to small changes in the signal and can resist the effects of noise and interference to a certain extent. In summary, orthogonal signal transform has significant advantages, and this paper proposes to use it to solve the spectral leakage problem.

[0008] Signal phase orthogonality holds great promise for future applications. Its significant role in waveform optimization and signal processing, coupled with the rapid development of emerging technologies such as the Internet of Things (IoT), 5G communication, and quantum computing, places higher demands on the accuracy, speed, and reliability of signal processing. Phase orthogonal technology, with its unique signal separation and anti-interference capabilities, will play an increasingly important role in these fields. In the communications field, technologies such as Orthogonal Frequency Division Multiplexing (OFDM) and Quadrature Amplitude Modulation (QAM) have become core to modern wireless communication systems, driving continuous improvements in data transmission rates and spectrum utilization. In radar and navigation, orthogonal phase-coded waveforms and orthogonal signal processing technologies will further improve the detection accuracy and anti-interference capabilities of radar systems, providing strong support for precision guidance and autonomous navigation. Furthermore, with the continuous advancement of microelectronics technology, the size of phase orthogonal devices will be further reduced, and their performance will be further improved, meeting the needs of portable devices and edge computing. Summary of the Invention

[0009] To address the problem that existing technologies cannot effectively solve the navigation denial issue caused by spectral aliasing of co-frequency / adjacent-frequency signals induced by power enhancement, the purpose of this invention is to provide a navigation anti-interference method based on orthogonal electric field polarization phase. Based on the fundamental principles of electromagnetic field theory and electromagnetic laws, the orthogonal electric field polarization phase method is used to achieve spatial domain isolation of signals at the radiation source, thereby suppressing mutual interference-type navigation denial.

[0010] This invention provides a navigation anti-interference method based on orthogonal electric field polarization phase, comprising:

[0011] Obtain the first and second signals from the BeiDou Navigation Satellite System;

[0012] The amplitude of the first signal is controlled by adjusting the gain factor to obtain the first gain signal;

[0013] The first gain signal and the second signal are linearly superimposed to obtain a dual-frequency signal:

[0014] Simulation was performed based on the dual-frequency signal to obtain an aliasing spectrum image;

[0015] When the characteristic peak of the second signal is not submerged by the first gain signal, the amplitude of the first signal is controlled by adjusting the gain factor.

[0016] When the characteristic peak of the second signal is submerged by the first gain signal, the critical value of the frequency band in which the first gain signal will cause energy leakage to the second signal is determined based on the characteristic peak.

[0017] Set both the first signal and the second signal to propagate along the z-axis to obtain the electric field strength of the first signal and the electric field strength of the second signal.

[0018] A first signal electric field is generated based on the first signal electric field strength, a preset frequency of the first gain signal, and a preset wavelength; a second signal electric field is generated based on the second signal electric field strength, a preset frequency of the second signal, and a preset wavelength.

[0019] The first signal electric field is horizontally polarized and the second signal electric field is vertically polarized, so that the spatial distribution of the electric fields of the dual-frequency signals are orthogonal in phase, and the dual-frequency signals are separated in the spatial domain through orthogonal polarization.

[0020] The dual-frequency signal that has reached the aliasing boundary condition is visualized to demonstrate the orthogonal polarization propagation characteristics;

[0021] Navigation anti-interference is performed based on the critical value and the orthogonal polarization propagation characteristics.

[0022] In one possible implementation, obtaining the first gain signal by controlling the amplitude of the first signal through adjusting the gain factor includes:

[0023] The first gain signal s is expressed by the following formula. B1C_enhanced (t):

[0024] s B1C_enhanced (t)=s B1C (t)G B1C_enhanced

[0025] In the formula, G B1C_linear t represents the adjusted gain factor and t represents time.

[0026] In one possible implementation, the step of controlling the amplitude of the first signal by adjusting the gain factor to obtain the first gain signal further includes:

[0027] The gain factor G is expressed by the following formula. B1C_dB :

[0028]

[0029] In the formula, P out For signal output power, P in This refers to the signal input power.

[0030] In one possible implementation, the step of linearly superimposing the first gain signal and the second signal to obtain a dual-frequency signal includes:

[0031] The dual-frequency signal s is expressed by the following formula. total (t):

[0032] s total (t)=s B1C_enhanced (t)+s B1I (t)

[0033] In the formula, s total (t)=s B1C_enhanced (t) represents the first gain signal, s B1I (t) represents the second signal, and t represents time.

[0034] In one possible implementation, setting both the first and second signals to propagate along the z-axis to obtain the electric field strength of the first and second signals includes:

[0035] The electric field strength of the first signal and the electric field strength of the second signal are calculated using the following formulas:

[0036]

[0037] In the formula, E0 is the electric field strength, P t For transmitted signal power, G t d is the gain of the transmitting antenna, and d is the distance from the receiving point to the transmitting source.

[0038] In one possible implementation, generating the first signal electric field based on the first signal electric field strength, a preset frequency of the first gain signal, and a preset wavelength, and generating the second signal electric field based on the second signal electric field strength, a preset frequency of the second signal, and a preset wavelength, includes:

[0039] The electric field of the first signal is calculated using the following formula.

[0040]

[0041] The electric field of the second signal is calculated using the following formula.

[0042]

[0043] In the formula, E 01 The first signal electric field strength, E 02 Let λ1 be the electric field strength of the second signal, λ2 be the wavelength of the electric field of the first signal, λ2 be the wavelength of the electric field of the second signal, f1 be the frequency of the first signal, f2 be the frequency of the second signal, t be time, and G be the electric field strength of the second signal. B1C_linear denoted as the gain factor after adjustment, and z represents the propagation direction.

[0044] In one possible implementation, the step of horizontally polarizing the first signal electric field and vertically polarizing the second signal electric field, so that the spatial distribution of the electric fields of the dual-frequency signals are orthogonal in phase, and the dual-frequency signals are separated in the spatial domain by orthogonal polarization, includes:

[0045] The vertical polarization electric field of the second signal electric field can be expressed by the following formula.

[0046]

[0047] The horizontal polarization electric field of the second signal electric field can be expressed by the following formula.

[0048]

[0049] In the formula, E 01 The first signal electric field strength, E 02 Let λ1 be the electric field strength of the second signal, λ2 be the wavelength of the electric field of the first signal, λ2 be the wavelength of the electric field of the second signal, f1 be the frequency of the first signal, f2 be the frequency of the second signal, t be time, and G be the electric field strength of the second signal. B1C_linear For the adjusted gain factor, For the horizontal polarization direction vector, is the vertical polarization direction vector, and z is the propagation direction.

[0050] In one possible implementation, the horizontal polarization direction vector is represented by the following formula.

[0051]

[0052] The vertical polarization direction vector is expressed by the following formula.

[0053]

[0054] In the formula, For the horizontal polarization direction vector, This is the vertical polarization direction vector.

[0055] In one possible implementation, the first signal is a B1I signal with a center frequency of 1561.098MHz, modulated using binary phase shift keying (BPSK).

[0056] In one possible implementation, the second signal is a B1C signal with a center frequency of 1575.42MHz, and is modulated using the orthogonal multiplexed binary offset carrier modulation method QMBOC.

[0057] The navigation anti-interference method based on electric field polarization phase orthogonality provided by this invention is based on the electromagnetic field theory and basic electromagnetic laws. It adopts the electric field polarization phase orthogonality method to achieve signal spatial domain isolation at the radiation source and suppress mutual interference-type navigation denial. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating a navigation anti-interference method provided in an embodiment of the present invention. Detailed Implementation

[0059] The embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. The following detailed description of the embodiments and the accompanying drawings are used to illustrate the principles of the present invention by way of example, but should not be used to limit the scope of the present invention. That is, the present invention is not limited to the described preferred embodiments, and the scope of the present invention is defined by the claims.

[0060] In the description of this invention, it should be noted that, unless otherwise stated, "a plurality of" means two or more; the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance; those skilled in the art can understand the specific meaning of the above terms in this invention as appropriate.

[0061] Figure 1 A flowchart illustrating the navigation anti-interference method provided in an embodiment of the present invention is shown below. Figure 1As shown, this invention provides a navigation anti-interference method based on orthogonal electric field polarization phases, comprising:

[0062] Step S1: Obtain the first and second signals from the BeiDou Navigation Satellite System;

[0063] In one possible implementation, the first signal is a B1I signal with a center frequency of 1561.098MHz, modulated using binary phase shift keying (BPSK). The second signal is a B1C signal with a center frequency of 1575.42MHz, modulated using quadrature multiplexed binary offset carrier modulation (QMBOC).

[0064] This invention primarily focuses on the aliasing phenomenon between the BeiDou system's B1I and B1C signals after B1C signal enhancement. The data code and ranging code have relatively low relevance to the focus of this study; therefore, the simulation does not consider the data code modulated on the carrier and its error correction coding method, nor the specific implementation method of the ranging code. Instead, a pseudo-random noise code (PRN code) model is used to generate a binary random sequence to simplify and replace the ranging code. Based on publicly available information and experimental requirements, the parameters of the B1I and B1C signals are reasonably set, as shown in Table 1.

[0065] Table 1

[0066]

[0067]

[0068] After reviewing the literature, it was determined that the center frequency of B1I is 1561.098MHz, using binary phase shift keying (BPSK) modulation; the center frequency of B1C is 1575.42MHz, using quadrature multiplexed binary offset carrier modulation (QMBOC). This modulation method combines BOC(1,1) and BOC(6,1) for composite modulation. BOC(1,1) shares some similarities in spectral characteristics and signal structure with GPS's L1C / A and Galileo's E1OS signals. By using the BOC(1,1) component as the core signal design, low- and mid-range receivers only need to process this component to achieve high interoperability with multi-system signals, which is beneficial for multi-system joint positioning and improves positioning accuracy and reliability. The introduction of the high-frequency BOC(6,1) component brings a larger root-mean-square bandwidth, theoretically possessing greater ranging potential. Its autocorrelation function has a narrower main peak and lower side lobes, which allows for more accurate measurement of signal propagation time during pseudocode ranging, thereby improving ranging accuracy and helping to achieve more precise positioning.

[0069] To generate BeiDou dual-frequency signals, this invention makes the following settings: the sampling rate is set to 100MHz to satisfy the Nyquist sampling theorem, and this frequency satisfies:

[0070] f s >2(f B1C +B)f s

[0071] Where B is the signal bandwidth, in order to avoid aliasing distortion.

[0072] The intermediate frequency (IF) was set to 25.42 MHz (B1C) and its frequency difference compensation value (B1I) to ensure the orthogonality of the signal in the digital domain. The Doppler frequency shift of the receiver under dynamic conditions was simulated by the frequency offset parameter ΔF, and its value was taken with reference to the maximum Doppler range (±50 kHz) of typical low-Earth orbit satellites.

[0073] The B1I signal generated in this invention adopts BPSK(2) modulation and uses a classic spread spectrum structure. The main code period is 2046 chips, superimposed with a 20-bit NH code. The navigation message is simulated by a pseudo-random sequence and modulated onto the data channel as follows:

[0074]

[0075] Among them, the NH code is the Neumann-Hoffman secondary code, which can effectively enhance the anti-interference performance of the signal in narrowband interference environment.

[0076] The B1C signal generation simulation employs a three-level modulation scheme, using QMBOC(6,1,4 / 33) modulation. In the baseband modulation layer, the data component is generated by BOC(1,1) modulation of the master code to produce a spreading sequence with a symbol rate of 1.023MHz. The pilot component uses a composite modulation scheme of BOC(1,1) and BOC(6,1) to generate a signal with time-domain orthogonality. Subcode modulation introduces a secondary encoding with a period of 10.23ms to improve signal acquisition sensitivity. The carrier modulation layer upconverts the baseband signal to an intermediate frequency of 25.42MHz, retaining both I and Q orthogonal components. The power combining layer weights and synthesizes the data and pilot components according to power ratios. Its mathematical expression is as follows:

[0077]

[0078] In the formula, P D P P1 P P2 These are the power allocation coefficients for the data component, pilot quadrature component, and pilot in-phase component, respectively, satisfying P D :P P1 :P P2 The power ratio is 1:29:4.

[0079] Step S2: The amplitude of the first signal is controlled by adjusting the gain factor to obtain the first gain signal;

[0080] In one possible implementation, the first gain signal s is represented by the following formula. B1C_enhanced (t):

[0081] s B1C_enhanced (t)=s B1C (t)G B1C_enhanced

[0082] In the formula, G B1C_linear t represents the adjusted gain factor and t represents time.

[0083] The gain factor G is expressed by the following formula. B1C_dB :

[0084]

[0085] In the formula, P out Signal output power (in Hz), P in This refers to the signal input power (in Hz).

[0086] This invention modifies the gain factor G. B1C_dB The linear gain factor G was obtained through quantitative calculation. B1C_linear The specific value allows for precise control of the signal amplitude. This gain applies to the baseband or intermediate frequency amplitude of the B1C signal, simulating scenarios where B1C signal power is enhanced in real-world systems.

[0087] Step S3: Linearly superimpose the first gain signal and the second signal to obtain a dual-frequency signal.

[0088] In one possible implementation, the dual-frequency signal s is represented by the following formula. total (t):

[0089] s total (t)=s B1C_enhanced (t)+s B1I (t)

[0090] In the formula, s total (t)=s B1C_enhanced (t) represents the first gain signal, s B1I (t) represents the second signal, and t represents time.

[0091] In one example, the impact of a B1C signal power boost on adjacent frequency bands in a real-world scenario is simulated. Power spectrum estimation is then performed using the Welch method, with a 500-point Hamming window, 50% overlap, and a 512-point FFT resolution. The intermediate frequency (IF) signal is restored to the radio frequency (RF) band by frequency shifting, and a normalized power spectral density map is plotted in the 1550-1600MHz range. A dynamic range of -265 to -220 dB / Hz is specifically set to clearly reveal the signal's detailed characteristics. Dual-frequency signal synthesis is achieved through linear superposition to simulate the impact of a B1C signal power boost on adjacent frequency bands in a real-world scenario.

[0092] Step S4: Simulate based on the dual-frequency signal to obtain the aliasing spectrum image;

[0093] In the aliasing analysis phase, simulation experiments quantify the interference level of the B1C signal on the B1I signal frequency band by adjusting its gain parameter. By incrementally increasing the B1C signal gain and repeatedly executing the signal synthesis and spectrum image generation process, a series of aliased spectrum images under different gains are generated. Observing the simulated aliased spectrum images, when the characteristic peaks of the B1I signal are observed to be submerged by the enhanced B1C signal, the critical value at which the enhanced B1C signal causes energy leakage into the B1I frequency band can be determined.

[0094] Step S5: When the characteristic peak of the second signal is not submerged by the first gain signal, return to controlling the amplitude of the first signal by adjusting the gain factor;

[0095] Step S6: When the characteristic peak of the second signal is submerged by the first gain signal, determine the critical value of the frequency band in which the first gain signal will cause energy leakage to the second signal based on the characteristic peak.

[0096] Step S7: Set both the first signal and the second signal to propagate along the z-axis to obtain the electric field strength of the first signal and the electric field strength of the second signal.

[0097] In one possible implementation, both the B1I and B1C signals are set to propagate along the z-axis, and the electric field intensity they generate is convenient for subsequent image observation and quantitative calculation and analysis.

[0098] The electric field strength is calculated using Friis's formula and the transmitting antenna power. Specifically, the electric field strength of the first signal and the electric field strength of the second signal are calculated according to the following formulas:

[0099]

[0100] In the formula, E0 is the electric field strength, P t For transmitted signal power, G t d is the gain of the transmitting antenna, and d is the distance from the receiving point to the transmitting source.

[0101] Step S8: Generate a first signal electric field based on the first signal electric field strength, the preset frequency and preset wavelength of the first gain signal, and generate a second signal electric field based on the second signal electric field strength, the preset frequency and preset wavelength of the second signal.

[0102] In one possible implementation, the frequencies (f1 = 1561.098 MHz, f2 = 1575.42 MHz) and corresponding wavelengths (λ1, λ2) of B1I (vertical polarization) and B1C (horizontal polarization) are set respectively. The wavelengths can be calculated using the following wavelength calculation formula:

[0103]

[0104] Where v is taken as the speed of light (v = 300,000,000 m / s), and the wavelength is calculated by substituting it into the center frequencies f1 and f2 of B1I and B1C:

[0105]

[0106] The electric field of the first signal is calculated using the following formula.

[0107]

[0108] The electric field of the second signal is calculated using the following formula.

[0109]

[0110] In the formula, E 01 The first signal electric field strength, E 02 Let λ1 be the electric field strength of the second signal, λ2 be the wavelength of the electric field of the first signal, λ2 be the wavelength of the electric field of the second signal, f1 be the frequency of the first signal, f2 be the frequency of the second signal, t be time, and G be the electric field strength of the second signal. B1C_linear denoted as the gain factor after adjustment, and z represents the propagation direction.

[0111] Step S9: The first signal electric field is horizontally polarized and the second signal electric field is vertically polarized, so that the spatial distribution of the electric fields of the dual-frequency signals are orthogonal in phase, and the dual-frequency signals are separated in the spatial domain by orthogonal polarization.

[0112] In one possible implementation, based on the fixed propagation direction of electromagnetic waves, the electric field polarization direction of the B1I and B1C signals can be controlled by setting a specific direction vector, thus ensuring the orthogonality of the electric field phase.

[0113] The horizontal polarization direction vector is expressed by the following formula.

[0114]

[0115] The vertical polarization direction vector is expressed by the following formula.

[0116]

[0117] In the formula, For the horizontal polarization direction vector, This is the vertical polarization direction vector.

[0118] The vertical polarization electric field of the second signal electric field can be expressed by the following formula.

[0119]

[0120] The horizontal polarization electric field of the second signal electric field can be expressed by the following formula.

[0121]

[0122] In the formula, E 01 The first signal electric field strength, E 02 Let λ1 be the electric field strength of the second signal, λ2 be the wavelength of the electric field of the first signal, λ2 be the wavelength of the electric field of the second signal, f1 be the frequency of the first signal, f2 be the frequency of the second signal, t be time, and G be the electric field strength of the second signal. B1C_linear For the adjusted gain factor, For the horizontal polarization direction vector, is the vertical polarization direction vector, and z is the propagation direction.

[0123] Based on the electromagnetic transverse wave characteristics, the signal propagation direction and the electric field oscillation direction satisfy orthogonal constraints. By setting the B1I and B1C signals to belong to horizontal or vertical linear polarization respectively, the spatial distribution of the electric fields of the dual-frequency signals is made phase-orthogonal, and the dual-frequency signals are separated in the spatial domain through polarization orthogonality. The horizontally polarized electric field and the vertically polarized electric field form an orthogonal distribution in three-dimensional space, physically blocking the spectral aliasing path. The vertically polarized component (B1I) is not affected by the enhancement of the horizontally polarized field, avoiding mutual interference at the source.

[0124] Step S10: Visualize the dual-frequency signal that has reached the aliasing boundary condition to demonstrate the orthogonal polarization propagation characteristics;

[0125] By setting up a dynamic demonstration, the orthogonal polarization propagation characteristics of dual-frequency signals that have reached the aliasing boundary conditions can be intuitively displayed.

[0126] This invention verifies the effectiveness of the orthogonal phase method in separating co-frequency interfering signals through joint time-frequency analysis and polarization domain processing. Simulation data shows that this method can increase the power of the B1C signal to the aliasing boundary value while maintaining the characteristics of the B1I signal, providing a theoretical basis for solving the problem of multi-signal coexistence in navigation denied environments.

[0127] Based on the orthogonality of electric field polarization phase, navigation denial is suppressed. The orthogonality of polarization significantly reduces the cross-correlation interference between the two signals, improving the success rate of navigation message parsing in the B1I band. No post-processing algorithm is required, and physical layer isolation enables fast response, meeting the anti-interference requirements in strong electromagnetic countermeasures scenarios and solving the navigation denial problem caused by co-channel / adjacent-channel signals.

[0128] Step S11: Perform navigation anti-interference based on critical values ​​and orthogonal polarization propagation characteristics.

[0129] The navigation anti-interference method based on electric field polarization phase orthogonality provided by this invention is based on the electromagnetic field theory and basic electromagnetic laws. It adopts the electric field polarization phase orthogonality method to achieve signal spatial domain isolation at the radiation source and suppress mutual interference-type navigation denial.

[0130] 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 technical scope 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 navigation anti-interference method based on orthogonal electric field polarization phase, characterized in that, include: Obtain the first and second signals from the BeiDou Navigation Satellite System; The amplitude of the first signal is controlled by adjusting the gain factor to obtain the first gain signal; The first gain signal and the second signal are linearly superimposed to obtain a dual-frequency signal: Simulation was performed based on the dual-frequency signal to obtain an aliasing spectrum image; When the characteristic peak of the second signal is not submerged by the first gain signal, the amplitude of the first signal is controlled by adjusting the gain factor. When the characteristic peak of the second signal is submerged by the first gain signal, the critical value of the frequency band in which the first gain signal will cause energy leakage to the second signal is determined based on the characteristic peak. Set both the first signal and the second signal to propagate along the z-axis to obtain the electric field strength of the first signal and the electric field strength of the second signal. A first signal electric field is generated based on the first signal electric field strength, a preset frequency of the first gain signal, and a preset wavelength; a second signal electric field is generated based on the second signal electric field strength, a preset frequency of the second signal, and a preset wavelength. The first signal electric field is horizontally polarized and the second signal electric field is vertically polarized, so that the spatial distribution of the electric fields of the dual-frequency signals are orthogonal in phase, and the dual-frequency signals are separated in the spatial domain through orthogonal polarization. The dual-frequency signal that has reached the aliasing boundary condition is visualized to demonstrate the orthogonal polarization propagation characteristics; Navigation anti-interference is performed based on the critical value and the orthogonal polarization propagation characteristics.

2. The navigation anti-interference method according to claim 1, characterized in that, The step of controlling the amplitude of the first signal by adjusting the gain factor to obtain the first gain signal includes: The first gain signal s is expressed by the following formula. B1C_enhanced (t): s B1C_enhanced (t)=s B1C (t)G B1C_enhanced In the formula, G B1C_linear t represents the adjusted gain factor and t represents time.

3. The navigation anti-interference method according to claim 2, characterized in that, The step of controlling the amplitude of the first signal by adjusting the gain factor to obtain the first gain signal further includes: The gain factor G is expressed by the following formula. B1C_dB : In the formula, P out For signal output power, P in This refers to the signal input power.

4. The navigation anti-interference method according to claim 1, characterized in that, The step of linearly superimposing the first gain signal and the second signal to obtain a dual-frequency signal includes: The dual-frequency signal s is expressed by the following formula. total (t): s total (t)=s B1C_enhanced (t)+s B1I (t) In the formula, s total (t)=s B1C_enhanced (t) represents the first gain signal, s B1I (t) represents the second signal, and t represents time.

5. The navigation anti-interference method according to claim 1, characterized in that, The step of setting both the first and second signals to propagate along the z-axis to obtain the electric field strength of the first and second signals includes: The electric field strength of the first signal and the electric field strength of the second signal are calculated using the following formulas: In the formula, E0 is the electric field strength, P t For transmitted signal power, G t d is the gain of the transmitting antenna, and d is the distance from the receiving point to the transmitting source.

6. The navigation anti-interference method according to claim 1, characterized in that, The step of generating a first signal electric field based on the first signal electric field strength, a preset frequency of the first gain signal, and a preset wavelength, and generating a second signal electric field based on the second signal electric field strength, a preset frequency of the second signal, and a preset wavelength includes: The electric field of the first signal is calculated using the following formula. The electric field of the second signal is calculated using the following formula. In the formula, E 01 The first signal electric field strength, E 02 Let λ1 be the electric field strength of the second signal, λ2 be the wavelength of the electric field of the first signal, λ2 be the wavelength of the electric field of the second signal, f1 be the frequency of the first signal, f2 be the frequency of the second signal, t be time, and G be the electric field strength of the second signal. B1C_linear denoted as the gain factor after adjustment, and z represents the propagation direction.

7. The navigation anti-interference method according to claim 1, characterized in that, The step of horizontally polarizing the first signal electric field and vertically polarizing the second signal electric field to make the spatial distribution of the electric fields of the dual-frequency signals orthogonal in phase, and separating the dual-frequency signals in the spatial domain through orthogonal polarization, includes: The vertical polarization electric field of the second signal electric field can be expressed by the following formula. The horizontal polarization electric field of the second signal electric field can be expressed by the following formula. In the formula, E 01 The first signal electric field strength, E 02 Let λ1 be the electric field strength of the second signal, λ2 be the wavelength of the electric field of the first signal, λ2 be the wavelength of the electric field of the second signal, f1 be the frequency of the first signal, f2 be the frequency of the second signal, t be time, and G be the electric field strength of the second signal. B1C_linear For the adjusted gain factor, For the horizontal polarization direction vector, is the vertical polarization direction vector, and z is the propagation direction.

8. The navigation anti-interference method according to claim 7, characterized in that, Also includes: The horizontal polarization direction vector is expressed by the following formula. The vertical polarization direction vector is expressed by the following formula. In the formula, For the horizontal polarization direction vector, This is the vertical polarization direction vector.

9. The navigation anti-interference method according to claim 1, characterized in that, The first signal is a B1I signal with a center frequency of 1561.098MHz, and it is modulated using binary phase shift keying (BPSK).

10. The navigation anti-interference method according to claim 1, characterized in that, The second signal is a B1C signal with a center frequency of 1575.42MHz, and it is modulated using the orthogonal multiplexed binary offset carrier modulation method QMBOC.

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