An ultrasonic radar pulse frequency orthogonal encoding method

Abstract

The application discloses an ultrasonic wave radar pulse frequency orthogonal coding method, which comprises the following steps: step 1, coding parameter configuration, including generating a frequency point set and setting a pulse duration and a pulse repetition interval according to a maximum non-ambiguous ranging requirement; step 2, setting a pulse frequency coding cost function; step 3, setting an analog annealing algorithm control parameter, generating a new solution through disturbance, setting a sidelobe ratio threshold value to remove, calculating a cost function value of the new solution, and determining whether to accept the new solution. The application introduces a wideband ambiguity function as a core evaluation basis of pulse frequency coding performance under the premise of meeting system parameter configuration and frequency resource constraints, and designs and selects the coding sequence through an optimization algorithm, so that the obtained coding presents a self-ambiguity function characteristic of concentrated main lobe energy and suppressed sidelobe level in a distance-speed two-dimensional plane, and meanwhile, a lower mutual ambiguity function peak level is maintained.

Description

Technical Field

[0001] This invention belongs to the field of radar technology, specifically ultrasonic radar, and more specifically to an orthogonal coding method for ultrasonic radar pulse frequencies. Background Technology

[0002] Co-frequency interference in ultrasonic radar refers to multiple radars operating in the same or very similar ultrasonic frequency band (mainly 40–70kHz), which easily leads to inaccurate ranging, false alarms, and missed detections. In scenarios involving multiple probes operating simultaneously within the same frequency band and dynamic target detection, radars face severe co-frequency interference. Furthermore, when the ratio of the target's radial velocity *r* relative to the radar to the sound wave propagation speed *r* is not negligible, the echo signal no longer exhibits a simple Doppler frequency shift but instead produces a significant time-domain scaling effect, thus generating ranging errors.

[0003] To address the aforementioned issues, a set of orthogonal coded signals with low autocorrelation sidelobes and low cross-correlation peaks is designed to effectively distinguish multi-probe signals within the same frequency band. The excellent orthogonality between the coded signals reduces cross-correlation interference between multi-probe echoes, effectively suppressing false targets and missed detections, thereby improving the system's resistance to co-frequency crosstalk in complex multi-probe environments. The coded signals are designed with sharp self-ambiguity function characteristics, thus improving the system's range and velocity resolution. By accurately compensating for the scale scaling effect caused by target velocity, coherent accumulation of echo signals can be achieved, leading to high-precision ranging.

[0004] In recent years, various methods have been proposed for the design of pulse orthogonal codes. The paper "Radar signal design for configuring a netted radar system with existing monostatic radar" uses an aperiodic correlation function as the cost function and employs optimization algorithms such as simulated annealing for code search. However, this method optimizes under the premise of a fixed set of reference signals, limiting the overall orthogonality of the coding group. The patent "MIMO Radar Orthogonal Waveform Design Method Based on Quantum Particle Swarm Optimization Algorithm" (Publication No.: CN113075623A) utilizes an improved quantum particle swarm optimization algorithm to simultaneously suppress waveform autocorrelation sidelobes and cross-correlation peaks. However, its optimization objective is mainly focused on the zero Doppler plane, making it difficult to guarantee comprehensive detection performance across the entire range-Doppler domain. The patent "A Low Pulse Pressure Sidelobe Continuous Nonlinear Frequency Modulated Waveform Design Method and Device Based on Simulated Annealing Algorithm" (Publication No.: CN119001619A) effectively reduces autocorrelation sidelobes by optimizing the ambiguity function performance of a single waveform, but it cannot simultaneously address the cross-correlation suppression capability between coding groups. The patent "A Waveform Design Method Based on Weighted Fuzzy Function" (CN116953643A) directly models and optimizes the two-dimensional shape of the fuzzy function and achieves differentiated control in the distance-Doppler plane through a weighted matrix. However, its continuous convex approximation strategy is highly dependent on the initial waveform and is prone to getting trapped in local optima.

[0005] In practical applications, existing methods often suffer from several problems: the generated pulse frequency coding groups may have insufficient autocorrelation performance or poor cross-correlation performance; furthermore, when using fuzzy functions as optimization targets, the temporal scaling effect of echo signals caused by target motion is often not fully considered, making the methods unsuitable for coding requirements in high-speed targets or ultrasonic scenarios. To address these issues, this invention proposes a pulse frequency orthogonal coding method based on broadband fuzzy functions. Summary of the Invention

[0006] This invention addresses the shortcomings of existing pulse frequency orthogonal coding design methods by proposing an orthogonal coding method. This method first rationally configures coding parameters according to the specific application scenario of the coded signal and parameter setting criteria, ensuring that the generated coded signal can adapt to actual detection requirements. Furthermore, it designs and optimizes the coding sequence based on a broadband fuzzy function and combines optimization algorithms to obtain a high-performance coded signal with low autocorrelation sidelobe peaks and low cross-correlation peaks.

[0007] The ultrasonic radar pulse frequency orthogonal coding method of the present invention includes the following steps: Step 1. Encoding Parameter Configuration Step 11. Set the encoding bit length according to the target scenario constraints. Obtain the transmitter's center frequency f0 and available bandwidth range B; Step 12. Generate a frequency point set; Step 13. Set the pulse duration Tp according to the radar's maximum unambiguous range; Step 2. Set the expression for the pulse frequency encoded signal as follows: , ; Where t is time, A n The amplitude corresponding to the nth pulse. For the coded symbol of the nth pulse, Let be the pulse repetition period, and Δf be the minimum frequency hopping interval. g() represents the time-domain envelope function of a single pulse; Set the cost function as follows: , This represents the velocity self-ambiguity function of the i-th coded signal. Let || denote the range self-ambiguity function of the i-th coded signal, || denotes the modulo operation; R is the target distance, v is the relative velocity between the radar and the target, M is the number of coded signals, and S... i For the i-th coded signal, This represents the cost function value; The function representing the mutual ambiguity between the i-th coded signal and the j-th coded signal; α is the weighting coefficient of the self-fuzzy function, and β is the weighting coefficient of the mutual fuzzy function; Step 3. Encoding Search Update: Step 31. Set the control parameters for the simulated annealing algorithm, including the initial high temperature T. start Termination temperature T end The cooling coefficient γ and the maximum number of iterations L in the internal circulation are set to zero; And randomly generate a set of initial encoding sequences in the solution space. ,S i This represents the transmitted signal of the i-th probe, serving as the current initial solution; And calculate its initial fitness based on the cost function obtained in step 2. As the initial cost function value J0(S) old ); Step 32. Perturbation generates a new solution: At the current temperature T, randomly apply the current encoding S old The transmitted signal S of any one of the probes i By performing random perturbation, a new encoded sequence is obtained. Generate candidate solution S newThe random perturbation includes randomly selecting a coding sequence. Two or more symbols in the sequence are swapped in their order within the sequence; When step 32 is executed for the first time, the current temperature is the initial high temperature T. start Each time step 32 is executed, the iteration count is incremented by 1; Step 33. Set the sidelobe ratio threshold ω for the newly generated encoded sequence. Calculate the maximum peak sidelobe ratio of the distance self-ambiguity function and the velocity self-ambiguity function. If the maximum peak sidelobe ratio is greater than the sidelobe ratio threshold ω, discard the current encoding sequence directly, do not perform subsequent cost calculations, and return to step 32 to generate a new solution. If the maximum peak sidelobe ratio is less than or equal to the sidelobe ratio threshold ω, proceed to step 34; Step 34. Calculate the cost function value of the new solution: For the filtered encoded sequences The fitness is calculated based on the cost function value obtained in step 2 as a new candidate solution. ; Step 35. Determine whether to include the new candidate solution. As the current solution; Step 36. Repeat until the calculated temperature reaches the termination temperature T. end The currently saved encoded sequence is output as the final transmitted signal encoding.

[0008] Preferably, step 13 specifically includes: Calculate the first unambiguous distance R max1 : ; Where c is the speed of radar wave, i.e., ultrasonic wave, in the medium, and T is the speed of radar wave, i.e., ultrasonic wave, in the medium. r The pulse repetition interval; Second unambiguous distance R max2 : ; The maximum unambiguous distance Rmax = min(Rmax1, Rmax2); when At that time, R re For the maximum detection range, further: If R max1 <R max2 Set the pulse repetition interval T r ,satisfy ; If R max1 >R max2 Adjust the pulse duration T p To satisfy .

[0009] Preferably, the self-fuzzy functions for velocity and distance are: ; in For transmission delay k is the scaling factor , This is the frequency-encoded signal for the transmitted pulse, where g() represents the time-domain envelope function of a single pulse, and * indicates taking the conjugate signal. The pulse repetition period, The bit depth of the encoded signal is represented by m and n, which represent the symbol sequence numbers within the encoded signal and have a range of values ​​of 1000. f n Let n be the carrier frequency of the nth pulse, defined as: , f is the coded symbol of the nth pulse. l The starting frequency is Δf, and the minimum frequency hopping interval is Δf. The expression for the mutual ambiguity function is: , in It is transmitting a signal. It's an interference signal. .

[0010] Preferably, the determination based on the Metropolis criterion in step 35 is as follows: The cost difference between calculating the old and new solutions And decide whether to accept a new solution according to the Metropolis criterion, where J(S old The previous solution is represented by the initial cost function value J0(S). For the first update, the previous solution is the initial cost function value J0(S). old ); like Then accept As the current solution; like With probability accept If the current solution is not accepted, it is retained. If the solution is deemed acceptable, then it is accepted. As the current solution; If the solution is not accepted, the current solution will not be updated.

[0011] Preferably, step 36 specifically includes: Step 361. Determine if the current iteration count KD has reached the maximum iteration count L; if not, return to step 32 to continue the search; if it has reached the maximum iteration count L, execute step 362. Step 362. Perform a cooling update operation T = T * γ, where γ is the cooling coefficient; and reset the current iteration number KD = 0; determine whether the updated current temperature T is lower than the termination temperature T. end , like If so, return to step 32 to proceed to the next cooling iteration; like If the condition is met, execution will stop, and the currently saved encoding sequence will be output as the final transmitted signal encoding.

[0012] Preferably, step 12 specifically includes: The intermediate code element of the corresponding coded code element in the coding sequence is set as the reference, the N-1 / 2th code element is selected as the intermediate code element, and the transmission frequency corresponding to the intermediate code element is set as the center frequency fc. Except for the intermediate symbol, the corresponding transmission frequency of the remaining symbols is based on fc. According to the relative position offset between the symbol and the intermediate symbol, the frequency is increased or decreased symmetrically in multiples of the minimum frequency hopping interval Δf. The frequency difference between adjacent symbols is the minimum frequency hopping interval Δf; the minimum frequency hopping interval Δf = B / (N-1).

[0013] Under the premise of meeting system parameter configuration and frequency resource constraints, this invention introduces a broadband ambiguity function as the core evaluation criterion for pulse frequency coding performance, and designs and filters the coding sequence through optimization algorithms so that the resulting code exhibits self-ambiguity function characteristics of concentrated main lobe energy and suppressed side lobe level in the distance-velocity two-dimensional plane, while maintaining a low mutual ambiguity function peak level.

[0014] The pulse frequency encoded sequence obtained by this invention possesses good orthogonality and distinguishability, effectively reducing cross-correlation interference under multi-probe or multi-coded signal conditions, and improving the system's anti-crosstalk capability from the coding level. Simultaneously, by introducing a scaling factor to compensate for the Doppler frequency shift caused by target motion, high-precision range and velocity parameter estimation is achieved. Attached Figure Description

[0015] Figure 1 This is a schematic flowchart illustrating a specific implementation of the orthogonal encoding method described in this invention; Figure 2 This is a flowchart illustrating a specific implementation of step 3 in the orthogonal coding method of the present invention; Figure 3 This is a schematic diagram of the fuzzy function of six sets of codes generated based on a specific embodiment of the orthogonal coding method described in this invention; Figure 4 This is a schematic diagram illustrating the fuzzy performance of the distance self-fuzzy function of six sets of codes generated based on a specific embodiment of the orthogonal coding method described in this invention. Figure 5 This is a schematic diagram illustrating the fuzzy performance of the speed self-fuzzy function of six sets of codes generated based on a specific embodiment of the orthogonal coding method described in this invention; Figure 6 This is a schematic diagram of the normalized cross-correlation matrix of six sets of codes generated based on a specific embodiment of the orthogonal coding method described in this invention. Detailed Implementation

[0016] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0017] The orthogonal coding method of the present invention includes the following steps: Step 1. Configure encoding parameters. Step 11: Set the number of encoding bits (fc) according to the target scenario constraints, and obtain the center frequency fc and available bandwidth range B of the transmitter.

[0018] The number of encoding bits N, i.e., the number of sub-pulses, and the center frequency and available bandwidth range B of the transmitter are set as needed; Step 12: Frequency point set generation.

[0019] The elements of the frequency point set of subpulse transmission are limited by the bandwidth range of the transmitter, that is, the frequency point of each subpulse must be within the interval [fc-B / 2, fc+B / 2]; where fc is the center frequency of the transmitter and B is the transmitter bandwidth.

[0020] The specific mapping rules for frequency points are as follows: Center symbol mapping: The middle symbol of the corresponding coded symbol in the encoded sequence is set as the reference. If the encoding length is N, then the ... As an intermediate symbol, the transmission frequency corresponding to the intermediate symbol is set as the center frequency fc.

[0021] Mapping of other symbols: For symbols other than the middle symbol, the corresponding transmission frequency is based on fc. According to the relative position offset between the symbol and the middle symbol, the frequency is symmetrically increased or decreased in multiples of the minimum frequency hopping interval Δf. The frequency difference between adjacent symbols is the minimum frequency hopping interval Δf, Δf=B / (N-1). For example, the frequency of the first symbol before the middle symbol is fc-Δf, the frequency of the first two symbols is fc-2*Δf, the frequency of the last symbol is fc+Δf, and the frequency of the last two symbols is fc+2*Δf; Step 13: Pulse duration selection.

[0022] The maximum unambiguous range of a radar is the farthest target distance that a pulse radar can unambiguously measure. The target echo must return to the radar before the next pulse is emitted; otherwise, range ambiguity will occur.

[0023] In this invention, the maximum unambiguous distance R max It is limited by two factors: the pulse repetition period and the minimum frequency hopping interval. The specific determination method is as follows: First unambiguous distance R max1 The pulse repetition interval T r The decision is based on the following relationship: ; Where c is the speed of radar wave, i.e., ultrasonic wave, in the medium, and T is the speed of radar wave, i.e., ultrasonic wave, in the medium. r The pulse repetition interval; Second unambiguous distance R max2 : ; The actual maximum unambiguous distance R max Take the smaller value between the first and second unambiguous distances mentioned above. That is, R max =min(R max1 R max2 ).

[0024] Assume the furthest distance to be detected is R. re , when hour, Furthermore, if By increasing the pulse repetition interval T r Make it satisfy To meet R re Requirements. If At that time, while keeping the number of encoded bits N constant and being limited by the bandwidth B, the pulse duration T is reduced. p To satisfy This eliminates the limiting effect of the minimum frequency hopping interval on the maximum unambiguous distance, thus satisfying R re Require.

[0025] When ranging is performed using the minimum frequency hopping interval Δf, the phase change of the target echo is linearly related to the distance. However, due to the inherent characteristics of phase... The periodicity of the measurement results leads to multiple values. The resulting maximum unambiguous distance is... That is, the target may appear in , Multiple locations, including This is the distance calculated at the current phase. Pulse duration. The distance gate of the signal in space is determined, and the distance that the pulse envelope can cover is... Only targets located within this distance can accumulate energy at the same sampling time. At the same distance gate, no phase ambiguity will occur, thus avoiding the phase ambiguity effect of frequency coding.

[0026] If R max1 >R max2 At that time, while keeping the number of encoded bits N constant and being limited by the bandwidth B, the pulse duration T is reduced. p To satisfy This eliminates the limiting effect of the minimum frequency hopping interval on the maximum unambiguous distance, thus satisfying R re Require.

[0027] when Time: No need to change T r and T p The value of .

[0028] Step 2, Encoding Performance Evaluation: The expression for the pulse frequency coded signal transmitted by this invention is as follows: , Where t is time, A n The amplitude corresponding to the nth pulse. For the coded symbol of the nth pulse, Let be the pulse repetition period, and Δf be the minimum frequency hopping interval. g() represents the time-domain envelope function of a single pulse; The assessment includes: The self-ambiguity function evaluation of the encoded signal is used to characterize the sidelobe level of a single encoded signal in the range and velocity dimensions; The cross-ambiguity function evaluation between coded signals is used to characterize the magnitude of the cross-correlation peak between different coded signals.

[0029] When the ratio of the relative velocity of the target to the radar wave velocity is not negligible, the fuzzy function evaluation is based on a broadband fuzzy function model to characterize the matching performance of the echo signal under the condition of time-domain scaling.

[0030] The cost function is:

[0031] --Formula 1 Self-fuzzy function constraint terms: This represents the velocity self-ambiguity function of the i-th coded signal. Let || denote the distance self-ambiguity function of the i-th coded signal, and || denote the modulo operation.

[0032] R is the target distance, v is the relative velocity between the radar and the target, M is the number of coded signals, and S is the distance between the radar and the target. i For the i-th coded signal, This represents the cost function value. By minimizing the maximum sidelobe of the self-ambiguity function, a sharp ambiguity function is obtained, thereby increasing the speed and distance measurement capabilities of a single coded signal.

[0033] Mutual fuzzy function constraint terms: Let $\frac{i}{j}$ represent the mutual ambiguity function between the $i$-th and $j$-th coded signals. By minimizing this cost function, the mutual interference between different coded signals is reduced, thereby improving the recognition capability in multi-probe scenarios.

[0034] The min operator before the objective function searches across all possible encoding sets to find the cost function that contains the maximum peak term of the mutually ambiguous function. The minimum value is obtained. Since the maximum amplitude of the cross-ambiguity function represents the strongest correlation amplitude that may occur between different coded signals in the distance-velocity space, i.e. the most severe crosstalk situation, when the maximum value is minimized as a whole, the optimization process will actively reduce the maximum cross-correlation peak value between each coded pair, thereby weakening the strongest interference component, reducing the correlation between different signals, and thus reducing the level of cross-interference.

[0035] α is the weighting coefficient of the self-ambiguity function, and β is the weighting coefficient of the mutual ambiguity function. In practical applications, the weighting coefficient is adjusted according to the emphasis on resolution or anti-interference capability required for detection. The ratio. For example, when higher resolution is required, α takes a larger value.

[0036] For high-speed moving target scenarios or ultrasonic detection scenarios, when the ratio of the target's velocity v to the wave velocity c is not negligible, considering that the target's motion not only causes Doppler frequency shift of the echo signal, but also causes the echo signal to stretch in the time domain, this invention uses a broadband fuzzy function as an evaluation index for parameter optimization.

[0037] Broadband self-fuzzy function in broadband fuzzy functions The mathematical expression is as follows: ; Where τ is the propagation delay k is the scaling factor , This is the frequency-encoded signal for the transmitted pulse, where g() represents the time-domain envelope function of a single pulse. * indicates taking the conjugate signal. The pulse repetition period, The bit depth of the encoded signal is represented by m and n, which represent the symbol sequence numbers within the encoded signal and have a range of values ​​of 1000. f n Let n be the carrier frequency of the nth pulse, defined as: , f is the coded symbol of the nth pulse. lΔf is the starting frequency, and Δf is the minimum frequency hopping interval.

[0038] The expression for the mutual ambiguity function is: ; --Formula 3; in It is transmitting a signal. It's an interference signal. For broadband signals, the relative motion of the target not only causes a Doppler shift in the echo signal but also leads to significant compression or expansion of the echo signal in the time domain. To accurately describe these effects, the broadband ambiguity function introduces a time delay τ and a scaling factor k, representing the range delay and time-domain scaling, respectively. The self-ambiguity function is used to analyze the matched filter output of the same signal at different (τ, k) values; its peak value corresponds to the target's true distance and velocity, while the sidelobes reflect the resolution and interference level. The cross-ambiguity function measures the correlation between different signals at the same (τ, k) value; a lower peak value indicates less crosstalk between signals. By optimizing the ambiguity function characteristics of the waveform, the anti-interference and target resolution capabilities of the system in high-dynamic environments can be effectively improved.

[0039] Substituting Equations 2 and 3 into Equation 1, and replacing the self-fuzzy function and the mutual fuzzy function respectively, the resulting cost function is: ; Defined by the scaling factor It can be seen that when k=1, the velocity v=0, and according to the definition of propagation delay... It can be seen that when τ=0, R=0. Therefore, the first term with coefficient α on the right side of the equal sign in Formula 4 corresponds to the distance self-fuzzy function in Formula 1 when the velocity is zero. The second term with coefficient α corresponds to the velocity self-fuzzy function when the distance is zero. The term with coefficient β is a mutually fuzzy function; Step 3, Encoding Search and Update Strategy: This step employs the simulated annealing algorithm, used to find the global optimum in large-scale optimization problems. Inspired by the solid-state annealing process in physics, the algorithm simulates the disordered motion of atoms at high temperatures, gradually cooling them to reach the lowest energy state. The core idea is to allow a certain probability of accepting solutions worse than the current one during the search process, thus avoiding getting trapped in local optima. As the "temperature" gradually decreases, the probability of accepting a worse solution also decreases, eventually converging to an approximate optimum.

[0040] Step 31. Set the core control parameters of the simulated annealing algorithm, including the initial high temperature T. start Termination temperature T endThe cooling coefficient γ and the maximum number of iterations L in the internal circulation are set to zero; And randomly generate a set of initial encoding sequences in the solution space. ,S i This represents the transmitted signal of the i-th probe, serving as the current initial solution. Here, the completeness of the initial encoding generation must be strictly constrained; that is, it must be ensured that all optional coded symbols are included in the initial encoding sequence.

[0041] Based on the cost function obtained in step 2, the initial encoded sequence is substituted into formula 4 to calculate its initial fitness. As the initial fitness J0(S) old This serves as a benchmark for subsequent optimizations.

[0042] Step 32. The perturbation generates a new solution: At the current temperature T, randomly select the current code S. old The transmitted signal S of any one of the probes i By performing random perturbation, a new encoded sequence is obtained. Generate candidate solution S new The random perturbation includes randomly selecting a coding sequence. Two or more symbols in the sequence are swapped in order.

[0043] When step 32 is executed for the first time, the current temperature is the initial high temperature T. start Each time step 32 is executed, the iteration count is incremented by 1; Step 33. Individual performance screening: Since orthogonal pulse frequency encoding requires that each encoded signal possess a thumbtack-shaped ambiguity function, a sidelobe ratio threshold ω is set to improve algorithm efficiency and ensure basic signal performance for the newly generated encoded sequence. Calculate the maximum peak sidelobe ratio of the distance self-ambiguity function and the velocity self-ambiguity function. If the maximum peak sidelobe ratio is greater than the sidelobe ratio threshold ω, discard the current encoding sequence directly, do not perform subsequent cost calculations, and return to step 32 to generate a new solution. If the maximum peak sidelobe ratio is less than or equal to the sidelobe ratio threshold ω, proceed to step 34.

[0044] Step 34. Calculate the cost function value of the new solution: For the filtered encoded sequences The fitness values ​​obtained through Formula 4 are used as new candidate solutions. ; Step 35. Metropolis Criterion Judgment: The cost difference between calculating the old and new solutions And decide whether to accept a new solution according to the Metropolis criterion, where J(S old The previous solution is represented by the initial fitness J0(S). For the first update, the previous solution is the initial fitness J0(S). old ); like If the new solution outperforms the old solution, then it is accepted. As the current solution; like This indicates that the performance of the new solution is worse, but it is not discarded directly; instead, it is determined by probability. accept If the current solution is not accepted, it is retained. The higher the current temperature T, the greater the probability of accepting a suboptimal solution, which means it helps to escape local optima; as the temperature decreases, the probability of acceptance begins to decrease.

[0045] If the solution is not accepted, the current solution will not be updated.

[0046] If the solution is deemed acceptable, then accept it. As the current solution.

[0047] Step 36. Inner loop iteration and cooling termination determination: Step 361. Determine whether the current iteration number KD has reached the maximum iteration number L; if not, it means that the system has not yet reached thermal equilibrium at the current temperature, then return to step 32 to continue the search; if it has reached, then execute step 362.

[0048] Step 362. Determining if cooling process terminates: Perform a cooling update operation T = T * γ, where γ is the cooling coefficient; reset the current iteration number KD = 0; and determine whether the updated current temperature T is lower than the termination temperature T. end， like If so, return to step 32 to proceed to the next cooling iteration; like If the condition is met, execution will stop, and the currently saved encoding sequence will be output as the final transmitted signal encoding.

[0049] A specific process for step 3 is as follows: Figure 2 As shown. Specific Implementation

[0050] This embodiment takes an ultrasonic radar with a center frequency fc=40kHz and a bandwidth B=3kHz as an example to determine the optimal pulse code signal parameters for an application scenario with a maximum detection distance of 6m. The specific steps are as follows: Step 1. Determine the parameters of the encoded signal: Step 11. Determine bandwidth and resolution Based on the probe's physical frequency response characteristics, the system's maximum usable bandwidth B is 3 kHz, covering a frequency range of 38.5 kHz to 41.5 kHz. To obtain optimal range resolution, this embodiment employs full-bandwidth coding design.

[0051] Step 12. Setting the encoding bit depth and frequency distribution Given a pulse code bit depth (i.e., number of sub-pulses) of N = 16, and a discrete frequency division within a finite bandwidth of B = 3kHz, the minimum frequency hopping interval Δf = 200Hz is determined. This establishes the set of discrete frequency points for the pulse-coded signal. .

[0052] Step 13. Determining Time Domain Parameters Pulse repetition period T r Determination of T: To cover a detection distance of 6m, take T as... r =40ms.

[0053] Pulse duration T p Determined: The maximum unambiguous distance is determined by the minimum frequency hopping interval. The detection distance is less than the required range, therefore set... ,set up .

[0054] Step 2. Perform performance evaluation on the generated candidate pulse frequency encoded sequences. The evaluation includes: self-ambiguity function evaluation of the encoded signals, used to characterize the sidelobe level of a single encoded signal in the distance and velocity dimensions; and mutual ambiguity function evaluation between encoded signals, used to characterize the magnitude of the correlation peak between different encoded signals. In this scenario, the ratio of the target's relative motion velocity to the wave velocity is not negligible. The ambiguity function evaluation needs to be based on a broadband ambiguity function model to characterize the matching performance of the echo signal under the condition of temporal scaling.

[0055] The cost function is: Self-fuzzy function constraint terms: The velocity self-ambiguity function of the i-th signal is represented. This represents the distance self-ambiguity function for the i-th signal. Mutual ambiguity function constraints: Let $\frac{i}{j}$ represent the mutual ambiguity function between the $i$-th and $j$-th coded signals. By minimizing this cost function, the mutual interference between different coded signals is reduced, thereby improving the recognition capability in multi-probe scenarios.

[0056] Dynamic weight allocation: α is the weight coefficient of the self-fuzzy function, and β is the weight coefficient of the mutual fuzzy function. In this scenario, high resolution and anti-interference capability are equally important; therefore, [the weight coefficient is chosen]. .

[0057] This embodiment uses a broadband fuzzy function as the evaluation index for parameter optimization. The broadband self-fuzzy function... The mathematical expression is as follows: ; Where τ is the propagation delay k is the scaling factor .

[0058] The expression for the mutual fuzziness function is:

[0059] Step 3. The steps for encoding the search and update strategy are as follows: Step 31. Set the core control parameters of the simulated annealing algorithm, initial high temperature. Termination temperature The maximum number of iterations in the inner loop is L=10000, and the cooling coefficient is... Furthermore, a set of initial encoding sequences is randomly generated within the solution space. This serves as the current initial solution. Here, the completeness of the initial code generation must be strictly constrained; that is, all optional code symbols must be included, and its initial fitness must be calculated according to the cost function of step B, serving as a benchmark for subsequent optimization.

[0060] Step 32. Perturbation generates a new solution: At the current temperature T, randomly apply the current encoding S old The transmitted signal S of one of the probes in the system i Perform random perturbation to generate candidate solutions S i The perturbation includes randomly selecting a coding sequence. Two or more symbols in a sequence are swapped in their order.

[0061] Step 33. Individual Performance Screening: To improve algorithm efficiency and ensure the basic performance of the signal, the newly generated encoded sequence is screened. Calculate the maximum peak-to-sidelobe ratio of its distance self-ambiguity function and velocity self-ambiguity function. If the peak-to-sidelobe ratio is greater than a threshold... If the code of the mutation is not used, the code is discarded and the subsequent cost calculation is not performed. The process returns to step 32 to generate a new solution. That is, the premise of orthogonal pulse frequency coding signal is that the individual coding signal has a fuzzy function similar to a thumbtack.

[0062] Step 34. Calculate the applicability of the new solution: For the filtered encoded sequences Using Formula 1, the fitness is used as a new candidate solution. ; Step 35. Metropolis Criterion Judgment: The cost difference between calculating the old and new solutions And decide whether to accept a new solution according to the Metropolis criterion, where J(S old The previous solution is represented by the initial fitness J0(S). For the first update, the previous solution is the initial fitness J0(S). old ); like If the new solution outperforms the old solution, then it is accepted. As the current solution; like This indicates that the performance of the new solution is worse, but it is not discarded directly; instead, it is determined by probability. accept If the current solution is not accepted, it is retained. The higher the current temperature T, the greater the probability of accepting a suboptimal solution, which means it helps to escape local optima; as the temperature decreases, the probability of acceptance begins to decrease.

[0063] If the solution is deemed acceptable, then accept it. As the current solution.

[0064] Step 36. Inner loop iteration and cooling termination determination: Step 361. Determine whether the current iteration number KD has reached the maximum iteration number L=100; if not, it means that the system has not yet reached thermal equilibrium at the current temperature, then return to step 32 to continue the search; if it has reached, then execute step 362.

[0065] Step 362. Cooling and Termination Judgment: Perform a cooling update operation T = T * γ, where γ is the cooling coefficient; reset the current iteration number KD = 0; and determine whether the updated current temperature T is lower than the termination temperature T. end , like If so, return to step 32 to proceed to the next cooling iteration; like If the condition is met, execution will stop, and the currently saved encoding sequence will be output as the final transmitted signal encoding.

[0066] The resulting six encoded signals, CODE1 to CODE6, are shown in the table below:

[0067] As shown in Figure 3, the broadband ambiguity functions corresponding to each group of codes all exhibit a typical "thumbtack" distribution characteristic, with the main lobe highly concentrated near zero delay and zero velocity, indicating that the coding design can achieve good focusing performance in both distance and velocity dimensions. Figure 3The three-dimensional fuzzy function morphology of six coded signals is shown. By optimizing the autocorrelation fuzzy function through minimizing the cost function in Equation 4, the sidelobe peaks are suppressed, thereby reducing the sidelobes of the distance and velocity fuzzy functions and forming a fuzzy function structure similar to a "thumbtack".

[0068] like Figure 4 Figure 4 shows a comparison of the distance self-ambiguity functions of each code when the speed is equal to 0. As can be seen from Figure 4, the distance self-ambiguity function curves of each code basically overlap. This is because the distance self-ambiguity function is mainly determined by the duration and bandwidth of a single pulse, and is independent of the order of the symbols. Figure 4 The autocorrelation characteristics of the six coded signals along the distance dimension are shown. It can be seen that the amplitude is largest at the central peak at 0 meters, while the side lobes are suppressed to below -10 dB. This is due to the [equation 1]... The sidelobe minimization of the term ensures good autocorrelation performance.

[0069] like Figure 5 The diagram shows a comparison of the self-ambiguity functions of each encoding distance when the distance is equal to 0. It can be seen that the sidelobe level of the velocity self-ambiguity function is effectively suppressed to about -10dB, showing good velocity sidelobe suppression capability. Figure 5 The autocorrelation characteristics of the six coded signals along the velocity dimension are shown. The central peak (at 0 m / s) has the highest amplitude, while the sidelobes are suppressed to below -8 dB, also as shown in Equation 1. The sidelobe minimization of the term ensures good autocorrelation performance.

[0070] Figure 6 shows the normalized cross-correlation matrices of the six codes. The peak values ​​of the normalized cross-correlation between different codes are all at a low level, indicating that the codes have good orthogonality and can effectively reduce mutual interference when multiple codes work in parallel.

[0071] Figure 6 This is a 6×6 cross-correlation matrix, where the diagonal lines represent the correlation (energy normalization value) of each signal with itself, and the off-diagonal lines represent the cross-correlation performance between different signals. The smaller the value, the lower the signal correlation and the stronger the anti-crosstalk capability. This can be achieved through formula 1. Minimizing the terms achieves strong resistance to crosstalk between different encoding methods.

[0072] The time-domain scaling is determined by k in Equation 2, which is the scaling factor. When a target moves away from the radar, the echo signal is stretched in the time domain and compressed when it moves closer. Traditional coding methods typically ignore the effect of this stretching factor, which has certain limitations. To address this, this invention introduces a broadband echo model that incorporates time-scale transformation based on Equation 2, overcoming this deficiency of traditional coding methods.

[0073] The foregoing descriptions are preferred embodiments of the present invention. Unless there is a clear contradiction between the preferred embodiments or a prerequisite for a particular preferred embodiment, the preferred embodiments can be arbitrarily combined and used. The embodiments and specific parameters described are only for clearly illustrating the inventor's invention verification process and are not intended to limit the scope of patent protection of the present invention. The scope of patent protection of the present invention shall still be determined by its claims. Similarly, any equivalent structural changes made based on the description and drawings of the present invention shall also be included within the scope of protection of the present invention.

Claims

1. An ultrasonic radar pulse frequency orthogonal coding method, characterized in that, Includes the following steps: Step 1. Encoding Parameter Configuration Step 11. Set the encoding bit length f according to the target scenario constraints, and obtain the transmitter's center frequency f0 and available bandwidth range B; Step 12. Generate a frequency point set; Step 13. Set the pulse duration Tp according to the radar's maximum unambiguous range; Step 2. Set the expression for the pulse frequency encoded signal as follows: ； Where t is time, A n The amplitude corresponding to the nth pulse. For the coded symbol of the nth pulse, Let be the pulse repetition period, and Δf be the minimum frequency hopping interval. g() represents the time-domain envelope function of a single pulse; Set the cost function as follows: , This represents the speed self-ambiguity function of the i-th coded signal. Let || denote the range self-ambiguity function of the i-th coded signal, || denotes the modulo operation; R is the target distance, v is the relative velocity between the radar and the target, M is the number of coded signals, and S... i For the i-th coded signal, This represents the cost function value; The function representing the mutual ambiguity between the i-th coded signal and the j-th coded signal; α is the weighting coefficient of the self-fuzzy function, and β is the weighting coefficient of the mutual fuzzy function; Step 3. Encoding Search Update: Step 31. Set the control parameters for the simulated annealing algorithm, including the initial high temperature T. start Termination temperature T end The cooling coefficient γ and the maximum number of iterations L in the internal circulation are set to zero; And randomly generate a set of initial encoding sequences in the solution space. ,S i This represents the transmitted signal of the i-th probe, serving as the current initial solution; And calculate its initial fitness based on the cost function obtained in step 2. As the initial cost function value J0(S) old ); Step 32. Perturbation generates a new solution: At the current temperature T, randomly apply the current encoding S old The transmitted signal S of any one of the probes i By performing random perturbation, a new encoded sequence is obtained. Generate candidate solutions S new The random perturbation includes randomly selecting a coding sequence. Two or more symbols in the sequence are swapped in their order within the sequence; When step 32 is executed for the first time, the current temperature is the initial high temperature T. start Each time step 32 is executed, the iteration count is incremented by 1; Step 33. Set the sidelobe ratio threshold ω for the newly generated encoded sequence. Calculate the maximum peak sidelobe ratio of the distance self-ambiguity function and the velocity self-ambiguity function. If the maximum peak sidelobe ratio is greater than the sidelobe ratio threshold ω, discard the current encoding sequence directly, do not perform subsequent cost calculations, and return to step 32 to generate a new solution. If the maximum peak sidelobe ratio is less than or equal to the sidelobe ratio threshold ω, proceed to step 34; Step 34. Calculate the cost function value of the new solution: For the filtered encoded sequences The fitness is calculated based on the cost function value obtained in step 2 as a new candidate solution. ; Step 35. Determine whether to include the new candidate solution. As the current solution; Step 36. Repeat until the calculated temperature reaches the termination temperature T. end The currently saved encoded sequence is output as the final transmitted signal encoding.

2. The ultrasonic radar pulse frequency orthogonal coding method as described in claim 1, characterized in that, Step 13 specifically involves: Calculate the first unambiguous distance R max1 : ； Where c is the speed of radar wave, i.e., ultrasonic wave, in the medium, and T is the speed of radar wave, i.e., ultrasonic wave, in the medium. r The pulse repetition interval; Second unambiguous distance R max2 : ； The maximum unambiguous distance Rmax = min(Rmax1, Rmax2); when At that time, R re For the maximum detection range, further: If R max1 <R max2 Set the pulse repetition interval T r ,satisfy ; If R max1 >R max2 Adjust the pulse duration T p To satisfy .

3. The ultrasonic radar pulse frequency orthogonal coding method as described in claim 1, characterized in that, The self-fuzzy functions for velocity and distance are: ； in For transmission delay k is the scaling factor , This is the frequency-encoded signal for the transmitted pulse, where g() represents the time-domain envelope function of a single pulse, and * indicates taking the conjugate signal. The pulse repetition period, The bit depth of the encoded signal is represented by m and n, which represent the symbol sequence numbers within the encoded signal and have a range of values ​​of 1000. f n Let n be the carrier frequency of the nth pulse, which is defined as: , f is the coded symbol of the nth pulse. l The starting frequency is Δf, and the minimum frequency hopping interval is Δf. The expression for the mutual ambiguity function is: , in It is transmitting a signal. It's an interference signal. .

4. The ultrasonic radar pulse frequency orthogonal coding method as described in claim 1, characterized in that, In step 35, the determination is based on the Metropolis criterion, specifically as follows: The cost difference between calculating the old and new solutions And decide whether to accept a new solution according to the Metropolis criterion, where J(S old The previous solution is represented by the initial cost function value J0(S). For the first update, the previous solution is the initial cost function value J0(S). old ); like Then accept As the current solution; like With probability accept If the current solution is not accepted, it is retained. ; If the solution is deemed acceptable, then accept it. As the current solution; If the solution is not accepted, the current solution will not be updated.

5. The ultrasonic radar pulse frequency orthogonal coding method as described in claim 1, characterized in that, Step 36 specifically involves: Step 361. Determine if the current iteration count KD has reached the maximum iteration count L; if not, return to step 32 to continue the search; if it has reached the maximum iteration count L, execute step 362. Step 362. Perform a cooling update operation T = T * γ, where γ is the cooling coefficient; and reset the current iteration number KD = 0; determine whether the updated current temperature T is lower than the termination temperature T. end , like If so, return to step 32 to proceed to the next cooling iteration; like If the condition is met, execution will stop, and the currently saved encoding sequence will be output as the final transmitted signal encoding.

6. The ultrasonic radar pulse frequency orthogonal coding method as described in claim 1, characterized in that, Step 12 specifically involves: The intermediate code element of the corresponding coded code element in the coding sequence is set as the reference, the N-1 / 2th code element is selected as the intermediate code element, and the transmission frequency corresponding to the intermediate code element is set as the center frequency fc. Except for the intermediate symbol, the corresponding transmission frequency of the remaining symbols is based on fc. According to the relative position offset between the symbol and the intermediate symbol, the frequency is increased or decreased symmetrically in multiples of the minimum frequency hopping interval Δf. The frequency difference between adjacent symbols is the minimum frequency hopping interval Δf; the minimum frequency hopping interval Δf = B / (N-1).

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