A method for estimating the velocity of a moving MPSK communication emitter

Abstract

The present invention relates to a method for estimating the speed of a moving MPSK communication radiation source. The method first divides the received MPSK signal into two paths. One path uses a minimum mean square error phase detection algorithm to estimate the motion phase deviation, compensate for the motion phase deviation, and demodulate the message symbols carried by the signal. The other MPSK signal is then segmented according to symbol synchronization information and symbol period. The phase of the symbol waveform corresponding to the demodulated message symbol is then compensated based on the demodulated message symbol. Finally, the phase-compensated symbol waveform data is combined into a two-dimensional matrix. The Doppler frequency of the data at the same sampling time of different symbols is calculated using a vertical Fourier transform method to obtain the speed of the moving target. Compared with traditional synaesthesia-integrated speed measurement methods, this method has the advantages of low detection probability and long range.

Description

Technical Field

[0001] The present invention belongs to the technical field of communication radiation source velocity estimation, and in particular relates to a method for estimating the velocity of a moving MPSK communication radiation source. Background Art

[0002] Traditional perception systems, such as radar, often rely on physical principles such as the Doppler effect to detect and track moving targets. Among them, MTI-MTD (Moving Target Indication-Moving Target Detection) technology, an effective moving target detection technique, compares radar signals across multiple scanning cycles and exploits the frequency difference between the moving target and the clutter to suppress ground clutter, enabling accurate detection and tracking of moving targets. This technology relies on the phase change of radar echoes as the target moves, providing a key basis for velocity estimation.

[0003] However, with the convergence of communication and sensing technologies, the requirements for velocity estimation methods are increasing. Traditional velocity estimation methods are often limited by specific application scenarios and signal conditions, making it difficult to achieve high-precision and robust velocity estimation. For example, some methods may be affected by the Rayleigh limit, making it difficult to accurately distinguish and estimate multiple overlapping moving targets in the velocity spectrum. Other methods may rely on specific signal processing methods, such as phase unwrapping, but in practical applications they may be limited by factors such as signal-to-noise ratio and target motion characteristics.

[0004] In recent years, in order to overcome these limitations, people have begun to explore new velocity estimation methods. Among them:

[0005] The patented method, "A Method for Estimating the Position and Velocity of Multiple Overlapping Moving Targets Based on SBRIM," extracts the amplitude and phase information of multi-channel signals from multiple overlapping moving targets in the image domain, constructs a linear observation model and corresponding measurement matrix, and leverages the sparsity of moving targets in the velocity spectrum. Using the SBRIM sparse reconstruction algorithm, the method achieves accurate position estimation and high-precision radial velocity estimation for multiple moving targets in low signal-to-noise ratio conditions. This method overcomes the Rayleigh limit, accurately estimating the true position of multiple overlapping moving targets in the velocity spectrum, and achieving high-precision velocity estimation.

[0006] The patent "Speed ​​Estimation Method Based on Phase Unwrapping" provides a speed estimation method based on phase unwrapping, which belongs to the field of radar signal processing of high-speed rendezvous target miss distance measurement system. First, the valid data frame containing target motion information is extracted according to the signal-to-noise ratio of the baseband echo signal. Secondly, the measured two-way distance corresponding to each sampling point of the target echo is obtained by phase unwrapping. Then, the search two-way distance corresponding to each sampling moment before the target hits the target is calculated. Taking into account that the target speed changes relatively slowly in the long-distance segment, the non-stationary characteristics of the signal are not obvious. The error between the search two-way distance and the measured two-way distance in this distance segment is used to reflect the deviation between the search speed and the target motion speed.

[0007] The patented "MIMO Radar Synaesthesia Integrated Waveform Design Method and Apparatus" initializes a phase coding sequence based on the communication signal to be transmitted and a preselected target MIMO radar to obtain an initial phase coding set. A target optimization problem is established based on a pre-constructed cost function, and the cost function is calculated based on the initial phase coding set to obtain the initial value of the target optimization problem. The target optimization problem is then solved using the initial value to obtain the target phase coding signal set. The cost function is constructed based on the target application scenario, and the target integrated waveform is obtained based on the target phase coding signal set. By changing the way communication information is embedded, the applicable conditions of the integrated waveform are reduced. The target integrated waveform is obtained by constructing and solving the target optimization problem. This waveform achieves both communication and perception simultaneously, eliminating the need to control the radar emission pattern during use.

[0008] However, the speed estimation methods in the above patents all have the problem of needing to transmit a detection signal and then process the received target reflection signal (echo) to obtain the target speed. Summary of the Invention

[0009] In order to solve the above technical problems, the present invention provides a method for estimating the speed of a moving MPSK communication radiation source. By directly receiving the transmission signal of the communication radiation source and performing cross-symbol processing on the received MPSK communication radiation source signal with the assistance of demodulation data, the target speed of the MPSK communication radiation source and its carrying platform is estimated, which solves the technical problem that traditional active methods need to transmit detection signals and receive target reflected echo signals for speed estimation.

[0010] In order to achieve the above object, the present invention adopts the following technical solutions:

[0011] A method for estimating the speed of an MPSK communication radiation source comprises the following steps:

[0012] MPSK signal processing: The received MPSK signal is processed in two ways;

[0013] Minimum mean square error phase detection: One signal uses the minimum mean square error phase detection algorithm to estimate the motion phase deviation and compensate for the motion phase deviation;

[0014] Demodulation of the received MPSK signal: Demodulate the compensated signal and provide the demodulated message symbols as data to another signal channel;

[0015] Data-assisted segmentation and phase compensation: The other MPSK signal is segmented according to symbol synchronization information and symbol period, and then the phase of the symbol waveform corresponding to the demodulated message symbol is compensated according to the demodulated message symbol;

[0016] Compensation signal combination two-dimensional matrix: the single symbol waveforms after phase compensation are combined into a two-dimensional matrix in a vertical arrangement;

[0017] Speed ​​measurement based on Doppler frequency: The Doppler frequency of data with different symbols at the same sampling time is calculated through the vertical Fourier transform method to obtain the speed of the moving target.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] 1. The present invention adopts a receiving-only method and does not transmit electromagnetic waves to the outside world, which has excellent concealment, reduces the risk of being discovered by the other party, and improves the security of the system.

[0020] 2. It has strong anti-electronic interference capabilities and is not easily discovered by the enemy, so the enemy cannot launch targeted electronic interference.

[0021] 3. It can realize the perception of wireless communication without adding a perception module, which reduces the complexity of the equipment, eliminates the need for secondary design of the waveform of the synaesthesia integrated signal waveform, and has a higher information transmission rate.

[0022] 4. The velocity resolution of the method of the present invention is greatly improved compared with the traditional method, and the performance is significantly reduced by the noise, and the detection performance under low signal-to-noise ratio is also guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 This is a schematic diagram of the signal segmentation principle.

[0025] Figure 2This is the schematic diagram of the speed estimation algorithm. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0027] See also Figure 1 and Figure 2 , an embodiment of the present invention provides a method for estimating the speed of a moving MPSK communication radiation source, the steps of which are as follows:

[0028] (1) MPSK signal processing: The MPSK radiation source signal is a communication signal formed by adding modulation information to the carrier phase by a digital baseband pulse. A variety of different carrier phases are used to represent the modulation information. MPSK signals are widely used in the field of communications. Usually, considering the complex signal model, the MPSK signal can be expressed as:

[0029]

[0030] Where, P t is the total signal power in the passband, is the complex modulation of the kth symbol, where A k is the normalized amplitude, θ k =[2q k +(1+(-1) M / 2 ) / 2]π / M is the phase modulation of the kth MPSK with independent and uniform distribution q k ∈{0,1,…,M-1}. T is the symbol period, θ c (t) is the carrier phase, p(t) is the pulse shape, and satisfies

[0031] Assuming that the target communication radiation source signal is stable during the observation time and the signal received at the observation station contains Doppler information, the received signal can be expressed as:

[0032]

[0033] Where, ω r =ω c +ω d ,ω c is the carrier frequency at the transmitting end, ω d is the frequency shift, and n(t) represents the noise term that obeys zero-mean Gaussian white noise.

[0034] (2) Minimum mean square error phase detection: The relative radial motion between the high-speed maneuvering target and the receiving terminal causes a serious Doppler effect. The demodulation of the communication radiation source signal under moving conditions and the demodulation conditions under stationary transmission conditions will be different due to the existence of the Doppler effect. The existence of the Doppler effect causes the system phase to change and is superimposed on the modulation signal phase of the digital phase modulation system, resulting in errors in demodulation phase judgment. Before demodulation, the signal is synchronized with the carrier phase, and the estimated carrier phase deviation is compensated for each symbol. In the demodulation system, assuming that symbol synchronization has been completed, each symbol is sampled at a normalized (symbol energy is 1) optimal sampling point:

[0035] r[K]=s[K]exp[j(2πΔfK+Δθ)]+n[K] (3)

[0036] Where s[K] is the modulation symbol, which is a point in the constellation diagram; Δf is the carrier frequency deviation; Δθ is the carrier phase deviation; and n[K] is the additive complex noise. If the modulation symbol s[K] and the complex noise power σ are known, 2 , then the conditional probability of r[K] with respect to the phase deviation Δθ(Δθ∈[-π,π)) is:

[0037]

[0038] Since it is a blind estimation, the receiver does not know the true value of s[K], but it can be reasonably assumed that the modulated data is a priori equally likely, that is, s[K] selects any constellation point c in QPSK i The prior probability of (i=0,1,2,3) is 1 / 4, so we can eliminate the irrelevant parameter s[K] by averaging and get

[0039]

[0040] According to the MMSE criteria, there are

[0041]

[0042] Finally, the MMSE estimate of Δθ can be obtained as:

[0043]

[0044] (3) Demodulation of the received MPSK signal: In QPSK modulation, there are four possible modulation phases: 0°, 90°, 180°, 270° or 45°, 135°, 225°, and 315°. These phases correspond to the bit combinations 00, 01, 11, and 10, respectively. QPSK demodulation is the inverse process of QPSK modulation, and its goal is to recover the original digital information from the received modulated signal.

[0045] Since a QPSK signal can be generated by superimposing two BPSK signals in phase and quadrature, demodulation involves coherently demodulating the two signals using BPSK. The resulting data is then converted from parallel to serial to obtain the transmitted baseband signal. IQ demodulation involves multiplying the received signal by a carrier with the same frequency and phase. Ideally, I-channel demodulation involves multiplying the received signal by cosω0t, while Q-channel demodulation involves multiplying the received signal by -sinω0t:

[0046]

[0047] After integration, two baseband signals, one in phase and one in quadrature, are obtained respectively. The original QPSK baseband signal is obtained by adding the two signals.

[0048] (4) Data-assisted segmentation and phase compensation: When reconnaissance targets with high-speed, uniform-speed radiation sources, the received signal is divided into several smaller time segments, as the radiation source does not have complex motion characteristics during movement. The length of each small segment is the duration of one symbol. Specifically, the signal segmentation criterion is that the length of each small segment is equal to the length of one symbol period.

[0049] In this segmentation method, Figure 2 Each S in the code element waveform represents a segmented signal. This segmentation method effectively detects and analyzes high-speed moving targets. Because each segmented signal contains complete symbol information, signal processing and analysis can be performed more accurately. This method not only simplifies the processing process but also improves the accuracy and efficiency of signal processing.

[0050] The signal received by the receiver has an inherent phase deviation due to the different symbols transmitted, and this phase deviation will undoubtedly cause a large error in the process of using phase to measure speed. Before performing Fourier transform, the original phase difference of the signal needs to be balanced. For QPSK signals, due to its special modulation method, there are four possible initial phases. Assuming that the phase modulation methods of 0°, 90°, 180°, and 270° are used, the θ corresponding to the '01' symbol is k is π / 2, and its expression can be expressed as:

[0051]

[0052] The θ corresponding to the other three symbols k They are 0, π and 3π / 2 respectively.

[0053] Next, we need to analyze the initial phase of each symbol. This step is to balance the initial phases of different symbols, that is, to subtract the initial phase θ corresponding to each symbol waveform. k, thus obtaining a phase-balanced signal.

[0054]

[0055] After this processing, the signal's phase information has been corrected, laying the foundation for subsequent Fourier transform analysis. This method eliminates the impact of initial phase differences between QPSK symbols on subsequent phase velocity measurement, improving the accuracy and reliability of signal processing. The time-domain expression for each symbol waveform can now be expressed as Equation (12).

[0056]

[0057] (5) Compensation signal combination two-dimensional matrix: select M segments from the segmented signal and align them vertically to generate a two-dimensional signal matrix. The horizontal length represents the number of sampling points for each segment of the signal, and the vertical length represents the number of symbols. M Each segmented signal is sampled by a two-dimensional matrix consisting of N points, S1 represents the segmented signal of the first symbol, S M Represents the segmented signal of the Mth symbol. In order to obtain a more descriptive representation, the two-dimensional matrix is ​​now expressed as (13):

[0058]

[0059] Each element y of the two-dimensional matrix M (N) is one of the sampling points of a segmented signal after the initial phase of formula (2). i (1)y i (2)…y i (N)] represents the N sampling point combinations of the i-th symbol, where i = 1, 2, ... M; any column [y1(j)y2(j) ... y M (j)] T represents the set of j-th sampling points of M symbols, where j = 1, 2, ... N, T Represents matrix transpose.

[0060] (6) Cross-symbol spectrum analysis: The Doppler effect introduces a linear phase shift between consecutive modulation symbols of the transmitted signal. This phenomenon provides a basis for velocity estimation. Velocity estimation is calculated based on the phase difference between adjacent symbols. This is because the frequency difference caused by motion is very small relative to the carrier frequency, and these changes cannot be accurately reflected directly on the spectrum peak through FFT. Doppler frequency shift f d With the movement speed and carrier frequency f c The relationship is: f d / f c=v / c, the speed of motion v is very different from the speed of light c, and the order of magnitude difference is generally 10 5 to 10 7 ,At this time, the accuracy requirement for directly estimating the Doppler shift is very high.

[0061] However, even subtle frequency variations can be clearly detected through phase shifts. The essence of velocity measurement based on the phase difference between adjacent symbols is that this phase difference is caused by the motion of the target object. If the target object is stationary, the Doppler shift will be zero, and there will be no phase difference between adjacent symbols. Conversely, when the target object is moving, the motion causes a Doppler shift, which in turn introduces a phase difference between adjacent symbols.

[0062] Assume that the target distance is R and the carrier frequency is f when transmitting. c At this time, the wavelength length can be obtained from the relationship between wavelength and frequency, λ = v / f. The phase of the received signal changes with distance as follows:

[0063]

[0064] This method uses the phase difference between adjacent symbols in the signal modulation process to infer the speed of the target object by measuring these phase differences. Because the Doppler shift is proportional to the speed of the target object and the frequency change can be reflected by the phase change, this method is very effective in speed estimation. Even in the case of small frequency changes, this method can provide reliable speed measurement results.

[0065] For applications in real-world environments, it must be expected that the received signal will experience a frequency shift due to the relative speed between the communication partners or between the radar platform and the reflecting object. v When moving, the peak point sequence value obtained by vertical FFT of any column of data is L, and the Doppler frequency shift f at the receiver is d for:

[0066] f d =ΔfL (15)

[0067] At this time, the speed is estimated from the Doppler frequency

[0068]

[0069] It can be seen that only f d , we can know the target's moving speed. The implementation flow chart of this method is as follows Figure 2 shown.

[0070] In actual measurement, the extraction of velocity by FFT algorithm is mainly the column vector FFT transformation in the two-dimensional matrix. For equation (13), any one of the columns Y′=[y1′(1),y2′(1),…,y′ M (1)] T Perform M-point FFT. According to Nyquist sampling theorem, to ensure accurate extraction of velocity information, f c / N≥2f d , the frequency resolution at this time is:

[0071]

[0072] Where f s is the sampling frequency, M is the number of symbols, and the speed resolution is:

[0073]

[0074] Where T is one symbol period.

[0075] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for estimating the velocity of a moving MPSK communication radiation source, characterized in that: The following steps are involved: MPSK signal processing: The received MPSK signal is processed in two ways; Minimum mean square error phase detection: One signal uses the minimum mean square error phase detection algorithm to estimate the motion phase deviation and compensate for the motion phase deviation; Demodulation of the received MPSK signal: Demodulate the compensated signal and provide the demodulated message symbols as data to another signal channel; Symbol waveform segmentation and data-assisted phase compensation: The other MPSK signal is segmented according to symbol synchronization information and symbol period, and then the phase of the symbol waveform corresponding to the demodulated message symbol is compensated according to the demodulated message symbol; Phase compensation signal combination two-dimensional matrix: the single symbol waveforms after phase compensation are combined into a two-dimensional matrix in a vertical arrangement; Velocity estimation based on Doppler frequency: The Doppler frequency of data with different symbols at the same sampling time is calculated by vertical Fourier transform to obtain the velocity of the moving target; The signal processing process is MPSK. The MPSK signal is expressed as: （1） Where, is the total signal power in the passband, It is k The complex modulation of symbols, where is the normalized amplitude, It is k MPSK phase modulation with independent and evenly distributed ; T is the symbol period, is the carrier phase, Pulse shape, meeting ; The target communication radiation source signal is stable during the observation time, and the signal received at the observation station contains Doppler information. The received signal can be expressed as: （2） Where, , is the carrier frequency at the transmitting end, is the frequency shift, represents the noise term that obeys zero-mean Gaussian white noise; The minimum mean square error phase detection algorithm is used to estimate the motion phase deviation of a signal and compensate for the motion phase deviation. Specifically, the carrier phase of the signal is synchronized before demodulation, and the estimated carrier phase deviation is compensated for each symbol. In the demodulation system, symbol synchronization has been completed, and each symbol is sampled at a normalized optimal sampling point: （3） Where, is the modulation symbol, which is a point in the constellation diagram; is the carrier frequency deviation; is the carrier phase deviation, ; is additive complex noise; if the modulation symbol is known Sum complex noise power ,So About phase deviation The conditional probability is: （4） According to the MMSE criteria, there are （6） available The MMSE is estimated as: （7） The other MPSK signal is segmented according to the symbol synchronization information and symbol period, and then the phase of the symbol waveform corresponding to the message symbol is compensated according to the demodulated message symbol. Specifically: For QPSK signal, due to its special modulation method, there are four possible initial phases; 、 、 、 Phase modulation mode, the '01' symbol corresponds to for , its expression can be expressed as: （10） This step is to balance the initial phases of different symbols, that is, to subtract the initial phase corresponding to each symbol waveform. , thus obtaining the phase-balanced signal （11）。 2. The method for estimating the velocity of a moving MPSK communication radiation source according to claim 1, wherein: The single symbol waveform after phase compensation is combined into a two-dimensional matrix in a vertical arrangement; specifically: the segmented signal is selected M segments and align them vertically to generate a two-dimensional signal matrix. The horizontal length represents the number of sampling points for each segment of the signal, and the vertical length represents the number of symbols. In order to obtain a more descriptive representation, the two-dimensional matrix is ​​now expressed as follows （13） Any row Indicates the i Symbols N sampling point combinations, where ; Any column express M The symbol j A set of sampling points, where , Represents matrix transpose.

3. The method for estimating the velocity of a moving MPSK communication radiation source according to claim 1, wherein: The Doppler frequency of the data of the same sampling time of different symbols is calculated by the vertical Fourier transform method to obtain the speed of the moving target. Specifically, the segmented signal two-dimensional matrix composed of the radiation source signal after phase balance is obtained. Each column of data is a sampling of different symbols at the same position. At this time, take any column of data and perform vertical FFT to obtain the peak point multiplied by the frequency resolution That is the frequency difference caused by the movement of the target radiation source; assuming that the two platforms move at a relative speed When moving, the peak point sequence value of FFT is , the Doppler shift at the receiver for: （15） In the formula , then the speed is estimated from the Doppler frequency: （16） Where, is the Doppler shift; is the carrier frequency; is the wavelength; is the speed of light; is the sampling frequency, is the number of symbols.

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