25 results about "Ambiguity function" patented technology

A method of processing communication signals for use in radar sensing includes segmenting copies of a reference signal and a received echo thereof into first- and second-length segments, respectively. The first- and second-length segments are arranged in respective first and second reference and echo matrices. First and second segmented ambiguity functions based on the first and second matrix pairs are evaluated. For obtaining first and second range estimates and first and second velocity estimates for one or more targets. Any ghost signal detected is resolved, or an ambiguity order is assigned thereto if resolving is not possible. The obtained or resolved range and velocity estimates, or the estimates and the assigned ambiguity order is output, and the evaluation process is iteratively repeated until a termination criterion is met. In the second and each further iteration a respective remaining right-most non-zero columns of the echo matrices are replaced with zero-columns.

The invention relates to the technical field of synthetic aperture radars, and discloses a dechirp strip SAR waveform design method based on time domain azimuth ambiguity, and the method comprises the steps: obtaining the azimuth output maximum width and synthetic aperture length of an SAR image through calculation; respectively calculating the minimum value and the maximum value of the pulse repetition frequency through the scene size and the synthetic aperture length so as to determine the initial selection range of the pulse repetition frequency; constructing a time domain azimuth ambiguity function, presetting a time domain azimuth ambiguity value, and traversing all pulse repetition frequency values in the pulse repetition frequency initial selection range through the time domain azimuth ambiguity function to obtain a candidate pulse repetition frequency set; in the candidate pulse repetition frequency set, the minimum value of the pulse repetition frequency is used as the final pulse repetition frequency, and the technical problems that the existing time domain azimuth ambiguity is not fully constrained, so that the SAR image has fuzzy artifacts, the imaging quality is influenced and the like are solved.

Embodiments of the present application provide a data processing method, device and equipment, the method comprising: obtaining a sequence set, the sequence set comprising a plurality of sequences, there being at least one first sequence among the plurality of sequences, the self ambiguity function of each first sequence being a thumbtack shape, the sidelobe energy of the cross ambiguity function between each first sequence and other sequences in the sequence set being less than a first threshold; transmitting a signal according to the sequences in the sequence set, the signal being used for speed measurement and / or distance measurement. The accuracy of radar measurement is improved.

A method and apparatus for sending a sequence, and a computing device. The method comprises: determining at least two types of reference signals; determining a number N of first sequences corresponding to the at least two types of reference signals, N being a positive integer greater than 1; determining a position sequence corresponding to the N first sequences; on the basis of the position sequence, determining positions of a number M of time units, the position sequence comprising M elements, the M elements being in one-to-one correspondence with the positions of the M time units, and M being a positive integer greater than 1 and less than or equal to N; and sending the N first sequences within the M time units, at least one first sequence being sent in each time unit of the M time units. In the described method, multiple existing types of reference signals can be reused to sense the position and speed of a detection target, and the sensing performance (i.e., the performance of an ambiguity function) can be improved while achieving integrated sensing and communication.

The embodiment of the invention provides a communication method and device, which are used for reducing the detection complexity while ensuring the detection performance of a PSS (Power System Stabilizer). According to the embodiment of the invention, the synchronization signal is generated based on the generalized Golay sequence, or the sequence used by the synchronization signal in the embodiment of the invention can be the generalized Golay sequence. A generalized Golay sequence element value set is {1,-1} and has a nested structure, and multiplication complexity required by related detection can be converted into addition complexity during detection, so that the detection complexity can be reduced. Moreover, the anti-frequency offset capability is generally evaluated by a fuzzy function sidelobe value, and the larger the fuzzy function sidelobe value is, the weaker the sequence anti-frequency offset capability is. In order to ensure the anti-frequency offset capability of the synchronization signal, the sidelobe value of the self-ambiguity function of the sequence used by the synchronization signal in the embodiment of the invention is relatively small, so that the anti-frequency offset capability of the synchronization signal is relatively strong, and the detection performance of the synchronization signal can be ensured.

This invention discloses a signal Doppler tolerance and sidelobe optimization method based on a weighted ambiguity function template. The method includes determining a discrete ambiguity function based on a two-dimensional ambiguity function of a continuous signal and a radar transmitted signal; obtaining matched filtering results for signals with different Doppler frequency shifts and determining the main lobe and sidelobe positions based on the Doppler frequency shift results; for the Doppler frequency shift case, establishing a cost function for Doppler tolerance optimization and a weighted cost function for joint optimization of Doppler tolerance and sidelobe based on the main lobe and sidelobe positions, respectively; setting the weight coefficients of the weighted cost function according to signal characteristic requirements to obtain the target cost function; and using simulation parameters for iterative updating to obtain the optimization result. This invention can improve signal Doppler tolerance while reducing signal sidelobes, significantly improving the practicality of random noise signals; and it allows for setting weight coefficients according to signal characteristic requirements to adjust the optimization ratio of signal Doppler tolerance and sidelobe, providing strong flexibility.

The invention discloses an anti-interference communication perception integrated waveform optimization method, and belongs to the field of wireless communication. The implementation method comprises the following steps: a transmitter generates a basic pseudo-random noise PRN code and generates a plurality of CSK symbols through cyclic shift, and a CSK modulation signal adopts a multi-system coding mode to enable data bits to correspond to various different code sequences, so that signal modulation is realized, and modulated communication information data is obtained; on the basis of a code shift keying CSK signal and a radar linear frequency modulation signal, a common-inductance integrated waveform is designed, the distance resolution and the detection distance of the radar can be improved on the premise of not increasing peak power, and CSK high-order modulation has higher frequency band utilization rate, high reliability and strong anti-interference capability; besides, the sidelobe level of the fuzzy function of the optimized anti-interference and inductance integrated waveform is lower, so that the dual targets of efficient communication and accurate perception can be realized in an integrated system, and excellent communication and radar performance is achieved.

An MIMO array sparse rapid design method of a fuzzy function generator based on deep learning comprises the following steps: firstly, directly learning a fuzzy function mapping relation corresponding to virtual array configuration and an incident angle by using a deep learning model so as to replace a traditional analysis fuzzy function calculation process depending on a manifold matrix; and then performing efficient performance evaluation on the candidate sparse array based on the fuzzy function generator, and obtaining a sparse array structure meeting the requirements of high resolution and low sidelobe in combination with an optimization strategy. By means of the technology, acceleration of more than 35 times can be achieved on the premise of not explicitly calculating the fuzzy function, the fuzzy function prediction root mean square error (RMSE) lower than 0.1 is kept, and therefore the sparse array design time is greatly shortened. Experiments on a 2T4R K-band MIMO radar prove that the designed array achieves 10 dB sidelobe level in a 100-degree field of view, the angular resolution is improved by about 32.8%, and the effectiveness and engineering application value of the method in high-resolution MIMO sparse array design are proved.

The invention provides an ISAC sequence generation method and device, and relates to the technical field of communication perception integration, and the method comprises the steps: obtaining a sequence length N and a sequence set size M, N being an odd number, M being a positive integer, and M being less than or equal to N; according to the sequence length N and the sequence set size M, sequence generation processing is carried out, a sequence set is obtained, the sequence set comprises M sequences, the length of each sequence ui is N, and the value of a sequence element ui (n) is an exponential function of a unit root omega N of modulus N. The sequence set in the application has a similar thumbtack type fuzzy function. In communication, the designed sequence can be used as a pilot frequency sequence of multiple users to realize channel estimation or synchronization; in the radar, the designed sequence set can be used for target perception.

The invention provides a time frequency estimation method based on SSA-VMD denoising, and relates to the technical field of passive positioning signal processing. The method comprises the following steps: acquiring a reference signal and an echo signal of a radiation source through a receiving station, optimizing key parameters (IMF number K and secondary penalty factor alpha) of variational mode decomposition (VMD) by using a sparrow search algorithm (SSA), and decomposing the signal through the optimized VMD algorithm to obtain an intrinsic mode function; the method comprises the following steps of: constructing an observation matrix and separating a signal source by taking the time difference as input of ICA (Independent Component Analysis), distinguishing useful signals and noise by combining permutation entropy (PE) and completing signal reconstruction, and finally realizing joint estimation of time difference and frequency difference based on a cross-ambiguity function. The method solves the problems of poor stability and poor signal denoising effect of traditional VMD parameter selection under a low signal-to-noise ratio, improves the accuracy and reliability of time-frequency estimation, and is suitable for a passive positioning system in a complex noise environment.

The application discloses a time-frequency difference parameter estimation algorithm based on RANSAC-WLS in a strong interference environment and belongs to the technical field of signal processing and target positioning. Firstly, a narrowband cross ambiguity function and a two-dimensional Fourier transform are used to extract candidate energy points; a RANSAC algorithm is used to construct a straight line model, iteratively screen an inlier point set, and effectively peel off interference outliers; based on the inlier points, a weighted least square method is used to optimize and solve ridge line parameters, and the bias influence of interference on estimation is eliminated; finally, combined with ridge line prior information, one-dimensional fine search is carried out through a wideband cross ambiguity function, and final time difference and scale difference are obtained. The application realizes effective discrimination of target features in a high interference environment, improves the algorithm theory breaking point to about 50%, and significantly enhances the robustness and accuracy of parameter estimation.

The invention relates to the technical field of underwater acoustic signal processing, in particular to a deep sea target sound source positioning system and method, and aims at solving the problem that a traditional DOA estimation positioning method has large errors. The invention provides a deep-sea target sound source positioning system and method. The method comprises the following steps: S1, performing two-dimensional plane conventional beam forming processing on a received deep-sea target signal to obtain a receiving arrival angle of the deep-sea target signal; s2, receiving arrival angle information according to the receiving arrival angle of the deep sea target, and reversely constructing a target position fuzzy surface in combination with an acoustic propagation model; s3, constructing a multi-path delay inequality fuzzy surface based on the propagation delay inequality of the receiving angle of arrival of the deep sea target among the multi-path paths; and S4, performing joint matching on the target position fuzzy surface in the S2 and the multi-path delay inequality fuzzy surface in the S3, and determining the accurate position of the target through a fuzzy function intersection point. According to the positioning system and method for the deep sea target sound source, the positioning precision is improved, and the error influence is reduced.

The invention discloses a cognitive sonar waveform design method using ambiguity function constraint, and belongs to the technical field of sonar target detection. According to the method, on the basis of a traditional water injection algorithm, a Q function representing reverberation output intensity is introduced to serve as a constraint condition on the target of maximizing the signal to interference and noise ratio (SINR); by deriving frequency domain expressions of a broadband ambiguity function, a narrowband ambiguity function and a Q function, constructing a nonlinear non-convex optimization model including SINR maximization, an equivalent bandwidth constraint (constant alpha), a Q function constraint (constant beta) and a transmitted waveform energy constraint (Ex); a fmincon solver (interior point method) in MATLAB is combined with a MultiStart global search mechanism to solve the model, and an optimal solution is selected through multiple times of random initialization to avoid initial value sensitivity. According to the waveform generated by the method, the Q function value at the Doppler frequency shift of the target can be reduced while the relatively high SINR is maintained, reverberation is effectively inhibited, and the shallow sea slow target detection performance is improved.

This invention discloses a method for calculating communication decoding performance based on a maximum likelihood detector, belonging to the field of radar-communication integration technology. First, the received signal is converted to the frequency domain. Then, detection statistics are derived based on the maximum likelihood detection criterion, and a communication decoder is established. Next, a communication ambiguity function is defined based on the detection statistics matched to a specific transmitted symbol and the received signal model. The communication ambiguity function directly reflects the impact of the signal waveform on decoding accuracy and can be used for theoretical analysis of decoding performance, especially providing guidance for waveform design in the context of radar-communication integration.

The invention discloses a multi-symbol STBC-LoRa joint radar communication system performance analysis method. According to the method, expressions of radar fuzzy functions of transmitted waveforms with different symbol numbers can be deduced, and the correctness of the expressions is verified through simulation. And simulation analysis of radar performance is carried out from the angles of radar echo processing and a fuzzy function. Simulation results show that the method not only can successfully identify the potential target through echoes, but also can reduce the PSLR of the delay dimension fuzzy function of the transmitted waveform along with the increase of the number of symbols, improve the Doppler resolution, and reduce the influence of cross correlation between antennas on the radar performance. Therefore, the radar performance can be synchronously improved under the condition of improving the communication rate. According to the method, a Rayleigh fading channel transmission model is constructed in a communication dimension, bit error rate characteristics of LoRa signals before and after coding are compared and analyzed, and it is found that the coded LoRa signals have more excellent bit error rate performance in a Rayleigh fading channel.

A communication method and apparatus. In the method, a first device determines one or more first sequences on the basis of information bits to be transmitted; and the first device sends a signal generated on the basis of the one or more first sequences. A sequence capacity corresponding to a first sequence is positively correlated with the cube of a sequence length, thereby increasing the sequence capacity and enabling carrying of more information. In addition, an ambiguity function corresponding to the first sequence is less than or equal to a threshold. Hence, the first sequence also has the characteristic of a low ambiguity zone, resulting in less interference and better error rate performance. Hence, in the method, a sequence having an increased sequence capacity and a low ambiguity zone characteristic is used to carry information bits, which are, for example, data, thereby improving the spectrum efficiency and providing better error rate performance.

This invention discloses a method for detecting weak scattered waves based on a complex-valued neural network, relating to the field of signal processing technology. The method includes: constructing a received signal model of a far-field multi-target signal source; constructing a complex-valued neural network model; segmenting data based on a receiving array antenna and known direct wave and scattered wave signals to obtain multiple corresponding direct wave and scattered wave signal segments; calculating multiple two-dimensional ambiguity functions based on the multiple direct wave and scattered wave signal segments; performing a maximum value search within the multiple two-dimensional ambiguity functions and extracting the maximum unit to construct a virtual snapshot; constructing a virtual covariance matrix based on the virtual snapshot; and inputting the virtual covariance matrix into the complex-valued neural network to obtain the direction-finding result of the weak scattered waves. This method not only improves the direction-finding accuracy of weak scattered waves but also enables the detection of coherent signals, achieving multi-target detection and enhancing the estimation effect of scattered waves.

The present application belongs to the field of radar technology, and relates to a radar radio frequency stealth method and system for low-interception design in space domain beam. The method comprises the following steps: constructing an encoding matrix of array element-pulse domain and a radar ambiguity function; configuring radar array parameters, setting a target direction of radar detection; calculating a basic scanning phase; constructing an expression of a basic low-gain directional diagram; generating a plurality of groups of low-gain directional diagrams of scanning directions; weighting and summing to obtain an expression of a target function of a high-gain directional diagram; and solving a weighting coefficient to obtain an expression of a synthesized high-gain directional diagram. The present application greatly reduces the interception probability of a high-gain beam by an enemy passive reconnaissance while ensuring the detection performance; the spatial distribution of a low-gain beam is naturally adapted to the high-gain synthesis requirement, a mathematical model of a high-gain detection beam and a weight value solving method are constructed through linear combination, the transmission with controllable low-interception risk is realized, and the performance balance of equivalent high-gain detection is achieved.

Embodiments of the present disclosure utilize signals generated by a radio frequency identification (RFID) antenna to locate the antenna. For example, a signal emitted by a transmitter can cause an unpowered mobile device's RFID antenna to generate return signals that are received by multiple antennas. Time difference of arrival (TDOA) and a frequency difference of arrival (FDOA) values can be calculated for the received signals. The calculated TDOA and FDOA values can be correlated using a cross ambiguity function (CAF). The correlated values can be plotted on a map to create a set of correlation maps. The correlation maps can be combined to produce an average map and the antenna can be located by identifying a maximum correlation value on the average map.

The application belongs to the field of radio detection, and particularly relates to a signal and data processing method of a multi-base incoherent scatter radar, and aims to solve the problem that the conventional signal and data processing method is invalid for the multi-base incoherent scatter radar. The application comprises: dividing the detection distance range of the multi-base incoherent scatter radar beam into multiple detection distance gates, and calculating the signal autocorrelation functions of the detection distance gates; after time correction of the signals at the receiving station, determining the observation system equation constant based on the antenna gains of the transmitting station and the receiving station, the detection common height, and the radar transmitting power; fitting the signal autocorrelation functions according to the spectral ambiguity function, the plasma scattering theory power spectrum function, the observation system equation constant and the statistical error of the signal autocorrelation functions, and inversely obtaining the ionospheric parameters of the detection distance gates. The application is applied to the multi-base incoherent scatter radar, and effective ionospheric multi-parameter results are obtained.

This invention belongs to the fields of underwater acoustic detection, underwater acoustic positioning, and sonar technology, and relates to a three-dimensional positioning method for targets in a direct sound zone based on a dual-horizontal array on the deep seabed. To solve the problem of three-dimensional positioning of near-surface moving line spectrum sound sources within a direct sound zone using a dual-horizontal array on the deep seabed, this invention obtains target azimuth estimation through beamforming of the dual-horizontal array; targets are estimated by tracking the maximum output power of the dual-horizontal array beams and the tracking azimuth angle; the estimated target distance, the preset sound source depth, and marine environmental parameters measured in actual marine experiments are input into a ray model to obtain the time delay difference between the direct path and the first reflection path from the sea surface, and a copy sound pressure field is constructed; finally, a depth estimation fusion ambiguity function for the dual-horizontal array is established, and its maximum value is the target depth. This invention is applicable to scenarios where the two horizontal arrays have arbitrary array configurations.

The invention belongs to the technical field of radiation source positioning and identification, and discloses a joint estimation method of a radiation source position and a modulation mode based on fractional order Fourier transform, which comprises the following steps: sampling a signal received by a ground receiving station, and then performing fractional order Fourier transform; combining the signal after fractional Fourier transform with a fuzzy function to construct a fractional cross fuzzy function; carrying out peak value search on the fractional order cross fuzzy function to obtain an optimal rotation angle; based on the optimal rotation angle, calculating corresponding time shift and frequency shift in a fractional order cross fuzzy function by using a Newton method, and converting the time shift and the frequency shift into real time difference of arrival and real frequency difference of arrival so as to complete radar radiation source positioning; and identifying the modulation type of the radar radiation source signal based on the optimal rotation angle and the peak characteristic of the fractional order cross-ambiguity function. According to the invention, target radiation positioning and identification in an electromagnetic environment with a low signal-to-noise ratio are realized.

The model and data double-driven interference suppression method disclosed by the application comprises: generating two non-stationary frequency modulation interferences; generating a signal of missing samples received by a receiver under a single interference and two interference conditions respectively; calculating a ambiguity function, smoothing the ambiguity function through an adaptive optimal kernel, and converting the smoothed ambiguity function into an autocorrelation function processed by the adaptive optimal kernel; sparsely reconstructing the interference by using an orthogonal matching pursuit algorithm to obtain an instantaneous frequency of the interference; correcting the instantaneous frequency of the interference by using a support vector regression; restoring the interference waveform by using the obtained instantaneous frequency, and removing the interference by using a subspace orthogonal projection method. The inaccurate non-stationary interference time-frequency characteristics obtained by sparse reconstruction are corrected by using the support vector regression, the imperfect instantaneous frequency is eliminated, the data information is fully utilized, the model driving and the data driving are combined, and the non-stationary interference suppression and elimination are realized.

The invention belongs to the technical field of radars, and relates to a wave path difference dynamic constraint-based fast point target detection and angle estimation method, which comprises the following steps of: performing conjugate multiplication on multi-pulse echo signals of two receiving antennas of a radar, and performing Fourier transform on a result to obtain a fuzzy function based on a wave path difference and a wave path difference change rate; performing zero setting operation on the fuzzy function on the dimension with the wave path difference change rate being zero, and removing static target signal components and static clutters; eliminating a cross term between a moving target signal component and a static target signal component by using a wave path difference change rate, and detecting a navigation point target signal; calculating an initial value of a wave path difference and a wave path difference change rate of the navigation speediness point target signal; and iteratively solving the maximum likelihood estimation for the Newton update expression by using the initial value to obtain an accurate wave path difference and a wave path difference change rate, and further calculating the angle of the navigation speediness point target. According to the invention, moving target detection and high-precision angle measurement in a zero Doppler scene are realized.

Provided in embodiments of the present application are a signal transmission method and apparatus, for use in reducing the detection complexity while ensuring the PSS detection performance. In the embodiments of the present application, a synchronization signal is generated on the basis of a generalized Golay sequence, or a sequence used by the synchronization signal may be the generalized Golay sequence. The elements of the generalized Golay sequence take values from the set {1, -1} and the generalized Golay sequence has a nested structure, and multiplication complexity required for related detection can be converted into addition complexity during detection, thereby reducing the detection complexity. In addition, an anti-frequency offset capability is generally evaluated on the basis of an ambiguity function sidelobe level, wherein the higher the ambiguity function sidelobe level, the lower the anti-frequency offset capability of a sequence. To ensure the anti-frequency offset capability of the synchronization signal, in the embodiments of the present application, an auto-ambiguity function sidelobe level of a sequence used by the synchronization signal is low, so that the synchronization signal has a strong anti-frequency offset capability, thereby ensuring the synchronization signal detection performance.