Motion MPSK communication radiation source speed estimation method

Abstract

The invention relates to a motion MPSK communication radiation source speed estimation method. The method comprises the following steps of: firstly, dividing a received MPSK signal into two paths, estimating motion phase deviation in one path by utilizing a minimum mean square error phase discrimination algorithm, compensating the motion phase deviation and demodulating a message symbol carried by the signal; carrying out signal segmentation on the other MPSK signal according to symbol synchronization information and a symbol period, and compensating a phase of a symbol waveform corresponding to a demodulated message symbol according to the demodulated message symbol; and finally, combining symbol waveform data after phase compensation into a two-dimensional matrix, and solving Doppler frequency for data of different symbols at the same sampling moment through a vertical Fourier transform method so as to obtain the speed of a moving target. Compared with a traditional sensing integrated speed measurement method, the method has the advantages of being low in probability of being found and long in operating distance.

Description

Technical Field

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

[0002] Traditional perception systems, such as radar systems, 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 is an effective moving target detection technology. By comparing radar signals of multiple scanning cycles, it uses the frequency difference between moving targets and clutter to suppress ground clutter, thereby achieving accurate detection and tracking of moving targets. This technology relies on the change in the phase of radar echoes when the target moves, providing an important basis for velocity estimation.

[0003] However, with the integration of communication and perception technologies, the requirements for velocity estimation methods are also increasing. Traditional velocity estimation methods are often limited by specific application scenarios and signal conditions, making it difficult to achieve high-precision and high-robust velocity estimation. For example, some methods may be affected by the Rayleigh limitation, 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 patent "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 of multiple overlapping moving targets in the image domain, constructs a linear observation model and a corresponding measurement matrix, and uses the sparsity of moving targets in the velocity spectrum to achieve accurate position estimation and high-precision radial velocity estimation of multiple moving targets under low signal-to-noise ratio conditions through the SBRIM sparse reconstruction algorithm. It can break through the Rayleigh limit, accurately estimate the true position of multiple overlapping moving targets in the velocity spectrum, and achieve 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 movement speed.

[0007] The patent "MIMO radar interaceptive integrated waveform design method and device" initializes the phase coding sequence according to the communication signal to be transmitted and the pre-selected target MIMO radar to obtain the initial phase coding set; establishes the target optimization problem according to the pre-constructed cost function, calculates the cost function according to the initial phase coding set to obtain the initial value of the target optimization problem, and solves the target optimization problem using the initial value to obtain the target phase coding signal set; the cost function is constructed according to the target application scenario; and the target integrated waveform is obtained according to the target phase coding signal set. By changing the way the communication information is embedded, the applicable conditions of the integrated waveform are reduced, and the target integrated waveform is obtained by constructing and solving the target optimization problem. One waveform realizes communication and perception at the same time, and there is no need to control the directional pattern of the radar emission when in 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. The method directly receives the transmission signal of the communication radiation source and performs cross-symbol processing on the received MPSK communication radiation source signal with the assistance of demodulation data to realize the estimation of the target speed of the MPSK communication radiation source and its carrying platform, thereby solving the technical problem that the traditional active method needs to transmit a detection signal and receive the target reflected echo signal 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 symbol as data auxiliary to another signal;

[0015] Data-assisted segmentation and phase compensation: 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;

[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 emit electromagnetic waves to the outside world, so it 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 influence of noise on its performance is also significantly reduced, 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 drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

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

[0025] Figure 2It 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 The embodiment of the present invention provides a method for estimating the speed of a moving MPSK communication radiation source.

[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 communication field. Usually, the complex signal model is considered. 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 uniformly distributed q k ∈{0,1,…,M-1}. T is the symbol period, θ c (t) is the carrier phase, p(t) is the pulse shape, satisfying

[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] In the formula, 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 differ 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 reasonably assume 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°, 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 the QPSK signal can be formed by superimposing two BPSK signals in phase and quadrature, the two signals are coherently demodulated as BPSK signals during demodulation, and the obtained data is finally converted from parallel to serial to obtain the transmitted baseband signal. For IQ demodulation, the received signal is multiplied by a carrier with the same frequency and phase. Under ideal conditions, the I-channel demodulation is to multiply the received signal by cosω0t, and the Q-channel demodulation is to multiply 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 detecting a high-speed uniform radiation source target, the received signal is divided into several smaller time periods because the radiation source does not have complex motion characteristics during movement. The length of each small segment is the duration of a symbol. Specifically, the signal segmentation standard is that the length of each small segment is equal to the length of a symbol period.

[0049] In this segmentation method, Figure 2 Each S in the code represents a segmented signal of a code element waveform. This segmentation method can effectively detect and analyze 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 receiving end has an inherent phase deviation due to the different symbols transmitted, and this phase deviation will undoubtedly bring great errors to the process of using phase to measure speed. Before 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 method of 0°, 90°, 180°, and 270° is 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 the signal is processed in this way, its phase information has been corrected, laying the foundation for the subsequent Fourier transform analysis. In this way, the influence of the initial phase difference between different QPSK symbols on the subsequent phase velocity measurement is eliminated, and the accuracy and reliability of signal processing are improved. At this time, the time domain expression of each symbol waveform can be expressed by 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 segment signal samples a two-dimensional matrix consisting of N points, S1 represents the segment 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) are all 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 based on the phase difference between adjacent symbols. This is because the frequency difference change 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: d / f c=v / c, the speed of motion v is very different from the speed of light c, the order of magnitude difference is generally 10 5 Up to 10 7 At this time, the accuracy of directly estimating the Doppler frequency shift is very high.

[0061] However, even a slight frequency change can be clearly shown by a phase change. The essence of using the phase difference between adjacent symbols for velocity measurement 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. On the contrary, when the target object moves, the motion causes a Doppler shift, which introduces a phase difference between adjacent symbols.

[0062] Assume the target distance is R and the carrier frequency is f 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 environments, it must be expected that the received signal will have 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 by 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 column Y′=[y1′(1),y2′(1),…,y′ M (1)] T Perform M-point FFT. According to the 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 a symbol period.

[0075] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope 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 received MPSK signal: demodulate the compensated signal and provide the demodulated message symbol as data auxiliary to another signal; Symbol waveform segmentation and data-assisted phase compensation: 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; 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; Speed ​​estimation 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.

2. The method for estimating the velocity of a moving MPSK communication radiation source according to claim 1, characterized in that: 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, assuming that the symbol synchronization has been completed, each symbol is sampled at a normalized (symbol energy is 1) optimal sampling point: r[K]=s[K]exp[j(2πΔfK+Δθ)]+n[K] (3) 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; 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: According to the MMSE criteria, there are The MMSE estimate of Δθ can be obtained as:

3. The method for estimating the velocity of a moving MPSK communication radiation source according to claim 1, characterized in that: 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 the QPSK signal, due to its special modulation method, there are four possible initial phases; assuming that the 0°, 90°, 180°, and 270° phase modulation methods are selected, the θ corresponding to the '01' symbol k is π / 2, and its expression can be expressed as: 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 the phase-balanced signal 4. The method for estimating the velocity of a moving MPSK communication radiation source according to claim 1, characterized in that: The single symbol waveform after phase compensation is combined into a two-dimensional matrix in a vertical arrangement; specifically: select M segments of 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. In order to obtain a more descriptive representation, the two-dimensional matrix is ​​now expressed as follows Any line [y 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.

5. The method for estimating the velocity of a moving MPSK communication radiation source according to claim 1, characterized in that: The Doppler frequency of the data at 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 signals after phase balance, each column of which is the sampling of different symbols at the same position. At this time, take any column of data for vertical FFT and multiply the peak point multiplied by the frequency resolution Δf is the frequency difference caused by the movement of the target radiation source; assuming that the two platforms move at a relative speed v, the peak point sequence value of FFT is L, and the Doppler frequency shift f at the receiver d for: f d =ΔfL (15) In the formula At this time, the speed is estimated by the Doppler frequency:

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