CN113835076B - Method, device, equipment and medium for optimally designing phase coding waveform group - Google Patents

Method, device, equipment and medium for optimally designing phase coding waveform group Download PDF

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CN113835076B
CN113835076B CN202111108734.8A CN202111108734A CN113835076B CN 113835076 B CN113835076 B CN 113835076B CN 202111108734 A CN202111108734 A CN 202111108734A CN 113835076 B CN113835076 B CN 113835076B
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waveform
phase
representing
code length
doppler frequency
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CN113835076A (en
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王福来
庞晨
王雪松
李永祯
封斯嘉
王占领
殷加鹏
李楠君
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National University of Defense Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/415—Identification of targets based on measurements of movement associated with the target
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The application relates to a method, a device, equipment and a medium for optimally designing a phase coding waveform group, wherein the method comprises the following steps: determining the code length of a phase coding waveform to be designed according to the maximum transmission signal duration and the transmission signal bandwidth of the system; determining a normalized Doppler frequency interval according to the detected target speed interval and the carrier frequency; taking a phase coding sequence of the phase coding waveform as a design variable, and constructing an optimization model of the phase coding waveform according to constraint conditions corresponding to code length, normalized Doppler frequency interval and design requirements; and solving the optimization model by using a model solver to obtain the optimized phase coding waveform with the code length. The method has the advantages of wider application range, higher waveform Doppler tolerance, low side lobe level, optimized distance and settable speed interval.

Description

Method, device, equipment and medium for optimally designing phase coding waveform group
Technical Field
The application relates to the technical field of radar detection, in particular to an optimization design method, device, equipment and medium for a phase coding waveform group.
Background
The orthogonal sequence group with good autocorrelation performance and cross correlation performance has wide application prospect in multichannel radar and communication systems. The reason is that when the waveform sequence has good autocorrelation sidelobes, the detection performance, synchronization performance, power control and the like of the system to a weak target can be improved. In addition, when the waveform sequence has low cross-correlation side lobes, the performances of clutter suppression, parameter identification, user differentiation and the like of the system can be improved.
The current waveform design method takes the peak side lobe ratio or the integral side lobe ratio of the correlation function as the optimization purpose, the peak side lobe ratio or the integral side lobe ratio of the correlation function is difficult to carry out optimization design simultaneously, the waveform optimization design difficulty is high, and in addition, the Doppler tolerance of the waveform is also high for the detection and the parameter measurement of a moving target. Aiming at the problem of designing the high Doppler tolerance orthogonal waveform group, the traditional solution is a constant-mode high Doppler tolerance waveform group design method which aims at reducing waveform sidelobe energy based on gradient, and the optimization of the waveform correlation performance between a specific speed and a range sidelobe is realized. However, in the process of implementing the present application, the inventor has found that the conventional waveform group design method has a technical problem that the doppler margin of the waveform cannot be effectively improved under the condition that the encoded waveform maintains good correlation performance.
Disclosure of Invention
Based on the foregoing, it is necessary to provide a phase code waveform group optimization design method, a phase code waveform group optimization design device, a computer device and a computer readable storage medium, which can achieve the purpose of effectively improving the doppler tolerance of the code waveform while maintaining good correlation performance.
In order to achieve the above object, the embodiment of the present application adopts the following technical scheme:
in one aspect, an embodiment of the present application provides a method for optimizing a phase encoding waveform set, including the steps of:
determining the code length of a phase coding waveform to be designed according to the maximum transmission signal duration and the transmission signal bandwidth of the system;
determining a normalized Doppler frequency interval according to the detected target speed interval and the carrier frequency;
taking a phase coding sequence of the phase coding waveform as a design variable, and constructing an optimization model of the phase coding waveform according to constraint conditions corresponding to code length, normalized Doppler frequency interval and design requirements;
and solving the optimization model by using a model solver to obtain the optimized phase coding waveform with the code length.
On the other hand, still provide a phase-encoding waveform group optimal design device, include:
the code length determining module is used for determining the code length of the phase coding waveform to be designed according to the maximum transmitting signal duration and the transmitting signal bandwidth of the system;
the frequency determining module is used for determining a normalized Doppler frequency interval according to the speed interval of the detection target and the carrier frequency;
the optimization construction module is used for constructing an optimization model of the phase coding waveform by taking the phase coding sequence of the phase coding waveform as a design variable according to constraint conditions corresponding to the code length, the normalized Doppler frequency interval and the design requirement;
and the optimization solving module is used for solving the optimization model by using the model solver to obtain the optimized phase encoding waveform with the code length.
In still another aspect, there is provided a computer device including a memory and a processor, the memory storing a computer program, the processor implementing the steps of the above-described phase-encoding waveform group optimization design method of any one of the above-described steps when executing the computer program.
In yet another aspect, there is also provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the above-described phase-encoding waveform group optimization design method of any one of the above.
One of the above technical solutions has the following advantages and beneficial effects:
according to the method, the device, the equipment and the medium for optimally designing the phase coding waveform group, the code length of the phase coding waveform to be designed is determined according to the maximum transmission signal duration and the transmission signal bandwidth of the system, then the normalized Doppler frequency interval is determined according to the detection target speed interval and the carrier frequency, the phase coding sequence of the phase coding waveform is further used as a design variable, an optimized model of the phase coding waveform is constructed according to constraint conditions corresponding to the code length, the normalized Doppler frequency interval and the design requirement, and finally a model solver is utilized to solve the optimized model, so that the optimized phase coding waveform with good correlation performance and the code length is obtained. Therefore, on the basis of determining system parameters, target parameters, waveform parameters and the like, a plurality of groups of phase coding waveforms with good Doppler tolerance and correlation performance can be designed by adjusting the target function of the model, the purpose of effectively improving the Doppler tolerance of the waveforms under the condition that the coding waveforms keep good correlation performance is realized, and the multi-target detection and parameter measurement of the multi-channel system are realized on the premise that the multi-channel system is not interfered with each other. Compared with the existing phase coding waveform design method, the method has the advantages of wider application range, higher waveform Doppler tolerance, low side lobe level, optimized distance and settable speed interval.
Drawings
FIG. 1 is a flow chart of a method for optimizing design of a phase encoding waveform set in one embodiment;
FIG. 2 is a flow chart of a method for optimizing a phase encoding waveform set according to another embodiment;
FIG. 3 is a schematic diagram of a self-blurring function of code 1 designed under constant modulus constraints in one embodiment;
FIG. 4 is a schematic diagram of a self-blurring function of code 2 designed under constant modulus constraints in one embodiment;
FIG. 5 is a graph of the mutual ambiguity function of code 1 and code 2 designed under constant modulus constraints in one embodiment;
FIG. 6 is a schematic diagram of a self-ambiguity function for code 1 designed under the constraint of η modulo in one embodiment;
FIG. 7 is a schematic diagram of a self-ambiguity function for code 2 designed under the constraint of η modulo in one embodiment;
FIG. 8 is a graph of the mutual ambiguity function of code 1 and code 2 designed under the constraint of η modulo in one embodiment;
FIG. 9 is a diagram of a self-ambiguity function for code 1 designed under the constraint of peak-to-average ratio in one embodiment;
FIG. 10 is a diagram of a self-ambiguity function for code 2 designed under the constraint of peak-to-average ratio in one embodiment;
FIG. 11 is a graph of the mutual ambiguity function of code 1 and code 2 designed under the constraint of peak-to-average ratio in one embodiment;
fig. 12 is a schematic block diagram of an apparatus for optimizing a phase encoding waveform set according to an embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
In addition, the technical solutions of the embodiments of the present application may be combined with each other, but it is necessary to be based on the fact that those skilled in the art can implement the technical solutions, and when the technical solutions are contradictory or cannot be implemented, it should be considered that the technical solutions are not combined, and are not within the scope of protection claimed by the present application.
The current waveform design method takes the peak sidelobe ratio or the integral sidelobe ratio of the correlation function as an optimization purpose, and is difficult to perform optimization design on the peak sidelobe ratio or the integral sidelobe ratio simultaneously. Meanwhile, in order to maximize the efficiency of the transmitting-end power amplifier, the transmitting waveform is often required to have specific non-male die constraint, which increases the difficulty of waveform optimization design and makes it difficult to obtain an optimal solution of waveform design. In addition, for the detection and parameter measurement of moving objects, in addition to the requirement that the waveform has good correlation performance, a high requirement is also put on the doppler tolerance of the waveform, that is, the waveform still needs to maintain good correlation characteristics in the presence of doppler shift.
The design method of the constant-mode high-Doppler tolerance waveform group based on the gradient and aiming at reducing the waveform side lobe energy is realized, although the optimization of the waveform correlation performance between specific speed and distance side lobe intervals is realized. However, the method can only design a constant-mode waveform, cannot be expanded to other common mode constraints, cannot optimize other common design indexes such as peak-to-side lobe ratio of the waveform, and the like, and limits the application of the method in detecting targets and measuring parameters in a multi-channel system on a multi-intensity moving target scene.
In summary, the present application provides an optimized design method of a phase code waveform set, which is capable of designing a phase code waveform set with good correlation performance and improving the doppler tolerance of the code waveform, aiming at the technical problem that the doppler tolerance of the code waveform cannot be effectively improved under the condition of maintaining good correlation performance of the code waveform in the conventional waveform set design method.
Referring to fig. 1, in one aspect, the present application provides a method for optimizing a phase encoding waveform set, including steps S12 to S18 as follows:
s12, determining the code length of the phase coding waveform to be designed according to the maximum transmission signal duration and the transmission signal bandwidth of the system.
It will be appreciated that the code length N of the phase-encoded waveform to be designed, i.e. the code length of the transmit waveform, is first determined from the maximum transmit signal duration (time width) T and the transmit signal bandwidth B of the system. Specifically, the code length N is:
N＝B×T
s14, determining a normalized Doppler frequency interval according to the detected target speed interval and the carrier frequency.
It will be appreciated that the minimum speed of the detected target and the maximum speed of the detected target may be determined from the detected target speed interval. The carrier frequency here may then be determined directly from the carrier frequency used by the radar detection system.
Specifically, according to the detected target speed interval and the carrier frequency, the normalized doppler frequency interval may be determined as follows:
wherein ,fmin Representing normalized DopplerLower frequency limit of frequency interval, f max Represents the upper frequency limit of the normalized Doppler frequency interval, N represents the code length, B represents the bandwidth of the transmitted signal, f 0 Represents the carrier frequency, c represents the speed of light, v min Representing the minimum speed of the detected target, v max Indicating the maximum speed of the detected object.
In some embodiments, as shown in fig. 2, after the step S14, the method may further include the following step S15:
s15, dividing the normalized Doppler frequency interval at equal intervals according to set intervals to form a plurality of Doppler frequency intervals.
Specifically, the Doppler frequency interval [ f min ,f max ]Divided into L segments at equal intervals of a set interval Deltaf, i.eEach bin can be represented as:
f l ＝f min +(l-1)·Δf,l＝1,…,L
thus, M groups of phase encoded signals u with code length N and bandwidth B m (t) can be expressed as:
wherein the phase code sequence is x m (n 1 )：
wherein ,am (n 1 ) Represents x m (n 1 ) Amplitude phi of phi m (n 1 ) Represents x m (n 1 ) T represents time. It will be appreciated that the phase code sequence x m (n 1 ) For the phase encoding sequence to be designed.
In some embodiments, in particular, the waveformAndis>Can be expressed as:
wherein ,(·)* Representing conjugate operation, phase coding sequenceAnd phase coding sequence->The method comprises the following steps of:
wherein ,representation->Amplitude of->Representation->N represents the code length,representation->Amplitude of->Representation->Phase of f l Frequency points representing normalized Doppler frequency bins, +.> and />Representing two different phase-coded sequences, respectively.
Alternatively, common waveform design constraints include a constant modulus constraint, an η modulus constraint, and a peak-to-average ratio constraint, which may be expressed as:
constant modulus constraint: i a m (n 1 )|＝C 1 (constant)
η -mode constraint: c (C) 1 -η 1 ≤|a m (n 1 )|≤C 1 +η 2 ,0≤η 1 ≤C 1 ,0≤η 2
Peak-to-average ratio constraint:
wherein I.I is a modulo operation, and I.I.I is vector 2-norm operation.
S16, taking the phase coding sequence of the phase coding waveform as a design variable, and constructing an optimization model of the phase coding waveform according to constraint conditions corresponding to the code length, the normalized Doppler frequency interval and the design requirement.
It can be understood that the phase coding sequence of the code waveform is taken as a design variable, an optimization index and a constraint condition are selected according to design requirements, an optimization model of the phase code waveform is constructed, and the phase code waveform with good correlation performance in a specified Doppler frequency shift interval is optimally designed.
Specifically, an optimization model of a phase-coded waveform set with good correlation performance for a specific doppler shift is constructed, and can be expressed as follows:
s.t.Ceq(x m )＝0,
C(x m )≤0,
x lb ≤x m ≤x ub
wherein ,
X＝[x 1 x 2 … x M ],x m ＝[x m (1) … x m (N)],m＝1,…,M
wherein ,xm Represents the phase code waveform, L represents the number of segments equally spaced apart from the normalized Doppler frequency interval, N represents the code length, M represents the number of groups of the phase code signal, f l Frequency points, w (n) 2 ,f l ) Representing the weighting factors of the side lobe intervals,representing waveform->And waveform->Is a mutual ambiguity function of Ceq (x m ) Representing an equality constraint, C (x m ) Representing inequality constraints, x lb and xub Respectively represent x m Lower and upper limit constraints of p e 2, + -infinity) is the energy selection factor.
When p=2, WSL (X) is equivalent to the conventional integral sidelobe ratio waveform design index, when p → +) in the case of infinity, the air conditioner is controlled, (WSL (X)) 1/p Then it is equivalent to the commonly used peak sidelobe ratio waveform design index.
And S18, solving the optimization model by using a model solver to obtain the optimized phase encoding waveform with the code length.
It will be appreciated that after the above-described optimization model is constructed, the optimization model may be automatically solved using solvers already known in the art.
Specifically, an fmincon solver in a Matlab tool can be used to solve an optimization model of a phase-coded waveform group with good correlation performance in a specific doppler frequency interval (such as the normalized doppler frequency interval), so as to obtain an optimized high-doppler-tolerance phase-coded waveform.
According to the method for optimizing the design of the phase coding waveform group, firstly, the code length of the phase coding waveform to be designed is determined according to the maximum transmission signal duration and the transmission signal bandwidth of the system, then, the normalized Doppler frequency interval is determined according to the detection target speed interval and the carrier frequency, and then, the phase coding sequence of the phase coding waveform is used as a design variable, an optimized model of the phase coding waveform is constructed according to constraint conditions corresponding to the code length, the normalized Doppler frequency interval and the design requirement, and finally, a model solver is utilized to solve the optimized model, so that the optimized phase coding waveform with good correlation performance and the code length is obtained. Therefore, on the basis of determining system parameters, target parameters, waveform parameters and the like, a plurality of groups of phase coding waveforms with good Doppler tolerance and correlation performance can be designed by adjusting the target function of the model, the purpose of effectively improving the Doppler tolerance of the waveforms under the condition that the coding waveforms keep good correlation performance is realized, and the multi-target detection and parameter measurement of the multi-channel system are realized on the premise that the multi-channel system is not interfered with each other. Compared with the existing phase coding waveform design method, the method has the advantages of wider application range, higher waveform Doppler tolerance, low side lobe level, optimized distance and settable speed interval.
In one embodiment, in order to more intuitively and fully describe the above-described phase-encoding waveform group optimization design method, an example in which experiments are performed using the above-described phase-encoding waveform group optimization design method is given below.
It should be noted that, the implementation examples given in the present specification are only illustrative, and not the only limitation of the specific embodiments of the present application, and those skilled in the art may apply the above-mentioned phase encoding waveform set optimization design method to realize experiments and waveform design applications in different application scenarios under the illustration of the implementation examples provided in the present application. Some of the specific parameters given in the examples below are by way of example only, and the values may be changed to suitable values accordingly in different embodiments.
The design framework applying the phase encoding waveform group optimization design method comprises the following parts:
(1) Determining the code length N of the phase coding waveform and the normalized Doppler frequency interval [ f ] according to the maximum transmitting signal time width, the transmitting signal bandwidth, the detection target speed interval, the carrier frequency and other parameters of the system min ，f max ]。
Specifically, firstly, according to the maximum transmission signal time width T and the transmission signal bandwidth B of the system, determining the code length of a transmission waveform as follows:
N＝B×T
further, according to the detection target speed section [ v min ，v max ]Carrier frequency f 0 Determining a normalized multiple frequency interval, which is:
wherein c is the speed of light. Thereby obtaining the waveform parameter N of the quadrature phase code waveform group and the normalized Doppler frequency interval f min ，f max ]。
(2) Based on the code length N and normalized Doppler frequency interval f min ，f max ]And constructing a phase coding waveform design model with good correlation performance in a specific Doppler frequency interval.
To simplify the analysis, doppler frequency interval [ f ] min ，f max ]Divided into L segments at equal intervals of interval Deltaf, i.eEach bin can be represented as:
f l ＝f min +(l-1)·Δf,l＝1,…,L
according to radar signal processing theory, M groups of phase coded signals with code length N and bandwidth B can be expressed as
wherein ,
for the phase coding sequence to be designed, a m (n 1) and φm (n 1 ) Respectively x m (n 1 ) Amplitude and phase of (a) are provided.
For a multichannel system, in order to realize the detection of an arbitrary single channel on a target, each waveform is required to have an autocorrelation function similar to an impulse function; in order to prevent the channels from interfering with each other, any two paths of waveforms are required to have all-zero cross-correlation functions; in order to achieve detection and measurement of moving objects, the waveform group is required to have good doppler tolerance. Thus, for a multi-channel system, the essence of the waveform design is to find the amplitude and phase sequences under constraints so that the encoded waveform set has good correlation properties.
Waveform according to radar signal processing theoryAndis>Can be expressed as:
wherein (·)* Is a conjugate operation:
further, common waveform design constraints include constant modulus constraint, η modulus constraint, and peak-to-average ratio constraint, which can be expressed as:
|a m (n 1 )|＝C 1 (constant)
C 1 -η 1 ≤|a m (n 1 )|≤C 1 +η 2 ,0≤η 1 ≤C 1 ,0≤η 2
Wherein I.I is a modulo operation, and I.I.I is vector 2-norm operation. For design purposes, constructing an optimized model of a set of phase-encoded waveforms with good correlation performance for a particular doppler shift can be expressed as:
s.t.Ceq(x m )＝0,
C(x m )≤0,
x lb ≤x m ≤x ub
wherein ,
X＝[x 1 x 2 … x M ],x m ＝[x m (1) … x m (N)],m＝1,…,M
and w (n) 2 ,f l ) Ceq (x) m ) Representing an equality constraint, C (x m ) Representing inequality constraints, x lb and xub Respectively represent x m Lower and upper limit constraints of p e 2, + -infinity) is the energy selection factor. When p=2, WSL (X) is equivalent to the conventional integral sidelobe ratio waveform design index, when p → +) in the case of infinity, the air conditioner is controlled, (WSL (X)) 1/p Then it is equivalent to the commonly used peak sidelobe ratio waveform design index.
(3) Aiming at the optimization model, the optimization model is solved by using an fmincon solver in Matlab to obtain a waveform optimization result under the constraint condition. Specifically, the call format of the fmincon solver is as follows
X＝fmincon(fun,X 0 ,A,b,Aeq,beq,lb，ub，nonlcon)
Wherein fun is an objective function, X 0 For the initial solution, A, b represents constraint A.X.ltoreq.b, aeq, beq represents constraint Aeq.X= beq, lb, ub represents the lower limit and upper line of the constraint, and nondlon represents the custom nonlinear constraint. For the optimization model of the method, fun is the objective function WSL (X), X 0 Can be generated by random initialization, i.e. X 0 ＝e j2 π·rand(N，M) Wherein rand (N, M) represents a value generated in [0,1 ]]The N multiplied by M dimensional matrix formed by random numbers uniformly distributed in the matrix, and the mode constraint conditions, namely constant mode constraint, eta mode constraint or peak-to-average ratio constraint, can be defined by the nondlon, so that the problem of waveform optimization design under the specific mode constraint condition is solved.
For example: typical parameters set are as follows: m=2, n=256,respectively at constant modulus constraint C 1 =1, η modulo constraint η 1 ＝η 2 =0.1 and peak-to-average ratio constraint PAR (x m ) And (3) selecting p=2, namely, the objective function is the integral sidelobe ratio, and the waveform blurring function obtained in the step (3) is shown in fig. 3-11. Specifically, the two self-blurring functions and the mutual blurring functions of the two groups of codes under the constant modulus constraint are respectively shown in fig. 3, fig. 4 and fig. 5, the two self-blurring functions and the mutual blurring functions of the two groups of codes under the eta modulus constraint are respectively shown in fig. 6, fig. 7 and fig. 8, and the two self-blurring functions and the mutual blurring functions of the two groups of codes under the peak-to-average ratio constraint are respectively shown in fig. 9, fig. 10 and fig. 11.
As can be seen from the exemplary design results, the correlation function of the designed waveform under each constraint has side lobes below-48 dB in the specified interval over the range of the pre-designed range and doppler frequency intervals, and the side lobe level of the designed waveform gradually decreases as the mode constraint is gradually relaxed, i.e., from the constant mode constraint to the peak-to-average ratio constraint. In summary, the above-mentioned technical problems have been solved by the above-mentioned design method, and since the designed waveform has extremely low side lobes, the detection and parameter measurement of the multi-channel system on the multi-moving object can be realized by using the design method.
According to the phase coding waveform group optimization design method, in the design process, proper objective functions and constraint conditions can be selected by adjusting model parameters according to actual system and application scene requirements, so that the method has better task adaptability.
The phase coding waveform set designed by the application can inhibit side lobes in a specific Doppler frequency interval and a specific distance side lobe interval according to an actual scene, realize extremely low side lobes in a concerned distance and speed interval, and is beneficial to the detection and parameter measurement of weak and small moving targets in a multi-moving target scene.
It should be understood that, although the steps in the flowcharts of fig. 1 and 2 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps of fig. 1 and 2 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily occur sequentially, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Referring to fig. 12, in one embodiment, there is further provided a phase encoding waveform set optimization design apparatus 100, including a code length determining module 11, a frequency determining module 13, an optimization construction module 15, and an optimization solving module 17. The code length determining module 11 is configured to determine a code length of a phase encoding waveform to be designed according to a maximum transmission signal duration and a transmission signal bandwidth of the system. The frequency determining module 13 is configured to determine a normalized doppler frequency interval according to the speed interval of the detection target and the carrier frequency. The optimization construction module 15 is configured to construct an optimization model of the phase-coded waveform according to constraint conditions corresponding to the code length, the normalized doppler frequency interval and the design requirement by using the phase-coded sequence of the phase-coded waveform as a design variable. The optimization solving module 17 is used for solving the optimization model by using a model solver to obtain the optimized phase encoding waveform with the code length.
The above-mentioned phase-encoding waveform group optimizing design device 100, through cooperation of each module, firstly determines the code length of the phase-encoding waveform to be designed according to the maximum transmission signal duration and the transmission signal bandwidth of the system, then determines the normalized doppler frequency interval according to the detection target speed interval and the carrier frequency, further uses the phase-encoding sequence of the phase-encoding waveform as a design variable, constructs an optimizing model of the phase-encoding waveform according to the constraint conditions corresponding to the code length, the normalized doppler frequency interval and the design requirement, and finally utilizes the model solver to solve the optimizing model to obtain the phase-encoding waveform with good correlation performance and the above-mentioned code length after optimization. Therefore, on the basis of determining system parameters, target parameters, waveform parameters and the like, a plurality of groups of phase coding waveforms with good Doppler tolerance and correlation performance can be designed by adjusting the target function of the model, the purpose of effectively improving the Doppler tolerance of the waveforms under the condition that the coding waveforms keep good correlation performance is realized, and the multi-target detection and parameter measurement of the multi-channel system are realized on the premise that the multi-channel system is not interfered with each other. Compared with the existing phase coding waveform design method, the method has the advantages of wider application range, higher waveform Doppler tolerance, low side lobe level, optimized distance and settable speed interval.
For specific limitations of the phase encoding waveform set optimization design apparatus 100, reference may be made to the corresponding limitations of the phase encoding waveform set optimization design method hereinabove, and detailed descriptions thereof are omitted herein. The above-described respective modules in the phase-encoding waveform group optimization design apparatus 100 may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be stored in a memory of the above device, or may be stored in software, so that the processor may call and execute operations corresponding to the above modules, where the above device may be, but is not limited to, various data analysis devices existing in the art.
In yet another aspect, a computer device is provided, including a memory storing a computer program and a processor, where the processor, when executing the computer program, may implement the steps of: determining the code length of a phase coding waveform to be designed according to the maximum transmission signal duration and the transmission signal bandwidth of the system; determining a normalized Doppler frequency interval according to the detected target speed interval and the carrier frequency; taking a phase coding sequence of the phase coding waveform as a design variable, and constructing an optimization model of the phase coding waveform according to constraint conditions corresponding to code length, normalized Doppler frequency interval and design requirements; and solving the optimization model by using a model solver to obtain the optimized phase coding waveform with the code length.
In one embodiment, the processor may further implement the steps or sub-steps added in each embodiment of the above-described method for optimizing the design of a phase encoding waveform group when executing the computer program.
In yet another aspect, there is also provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of: determining the code length of a phase coding waveform to be designed according to the maximum transmission signal duration and the transmission signal bandwidth of the system; determining a normalized Doppler frequency interval according to the detected target speed interval and the carrier frequency; taking a phase coding sequence of the phase coding waveform as a design variable, and constructing an optimization model of the phase coding waveform according to constraint conditions corresponding to code length, normalized Doppler frequency interval and design requirements; and solving the optimization model by using a model solver to obtain the optimized phase coding waveform with the code length.
In one embodiment, the computer program may further implement the steps or sub-steps added in each embodiment of the above-described method for optimizing a phase encoding waveform group when executed by a processor.
Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of a computer program, which may be stored on a non-transitory computer readable storage medium, that when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus dynamic random access memory (Rambus DRAM, RDRAM for short), and interface dynamic random access memory (DRDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it is possible for those skilled in the art to make several variations and modifications without departing from the spirit of the present application, which fall within the protection scope of the present application. The scope of the application is therefore intended to be covered by the appended claims.

Claims (10)

1. The phase coding waveform group optimization design method is characterized by comprising the following steps:
determining the code length of a phase coding waveform to be designed according to the maximum transmission signal duration and the transmission signal bandwidth of the system;
determining a normalized Doppler frequency interval according to the detected target speed interval and the carrier frequency;
encoding the phase of the waveform with the phaseThe bit coding sequence is a design variable, and an optimization model of the phase coding waveform is constructed according to constraint conditions corresponding to the code length, the normalized Doppler frequency interval and design requirements; the phase code sequence is x m (n 1 )：
wherein ,am (n 1 ) Represents x m (n 1 ) Amplitude phi of phi m (n 1 ) Represents x m (n 1 ) N represents the code length;
and solving the optimization model by using a model solver to obtain the optimized phase encoding waveform with the code length.
2. The phase-encoding waveform set optimization design method according to claim 1, wherein the optimization model is:
s.t.Ceq(x m )＝0,
C(x m )≤0,
x lb ≤x m ≤x ub
wherein ,
X＝[x 1 x 2 …x M ],x m ＝[x m (1)…x m (N)],m＝1,…,M
wherein ,xm Representing the phase code waveform, L representing the number of segments equally spaced apart from the normalized Doppler frequency interval, N representing the code length, M representing the number of groups of phase code signals, f l Frequency points, w (n) 2 ,f l ) Representing the weighting factors of the side lobe intervals,representing waveform->And waveform->Is a mutual ambiguity function of Ceq (x m ) Representing an equality constraint, C (x m ) Representing inequality constraints, x lb and xub Respectively represent x m Lower and upper limit constraints of p e 2, + -infinity) is the energy selection factor.
3. The phase-encoding waveform group optimization design method according to claim 1 or 2, wherein the determined code length is:
N＝B×T
wherein N represents the code length, B represents the transmission signal bandwidth, and T represents the maximum transmission signal duration.
4. The method for optimizing design of a phase-coded waveform set according to claim 3, wherein the normalized doppler frequency interval is:
wherein ,fmin A lower frequency limit, f, representing the normalized Doppler frequency interval max Representing the upper frequency limit of the normalized Doppler frequency interval, N representing the code length, and B representing the transmissionBandwidth of radio signal f 0 Represents the carrier frequency, c represents the speed of light, v min Representing the minimum speed of the detected target, v max Indicating the maximum speed of the detected object.
5. The method for optimizing design of phase-coded waveform set according to claim 3, further comprising, after the step of determining the normalized doppler frequency interval according to the detection target speed interval and the carrier frequency:
dividing the normalized Doppler frequency interval at equal intervals according to a set interval to form a plurality of Doppler frequency intervals;
the set interval is Δf:
wherein ,fmin A lower frequency limit, f, representing the normalized Doppler frequency interval max And (3) representing the upper frequency limit of the normalized Doppler frequency interval, and L representing the number of segments equally spaced from the normalized Doppler frequency interval.
6. The method for optimizing a phase-encoded waveform set according to claim 2, wherein the mutual blurring functionThe method comprises the following steps:
wherein ,(·)* Representing conjugate operations and phase encoding sequencesAnd phase coding sequence->The method comprises the following steps of:
wherein ,representation->Amplitude of->Representation->N represents the code length,representation->Amplitude of->Representation->Phase of f l Frequency points representing the normalized Doppler frequency interval, < >> and />Representing two different phase-coded sequences, respectively.
7. The method of claim 1, wherein the model solver is a fmincon solver.
8. An apparatus for optimally designing a phase-encoded waveform group, comprising:
the code length determining module is used for determining the code length of the phase coding waveform to be designed according to the maximum transmitting signal duration and the transmitting signal bandwidth of the system;
the frequency determining module is used for determining a normalized Doppler frequency interval according to the speed interval of the detection target and the carrier frequency;
the optimization construction module is used for constructing an optimization model of the phase coding waveform by taking the phase coding sequence of the phase coding waveform as a design variable according to constraint conditions corresponding to the code length, the normalized Doppler frequency interval and the design requirement; the phase code sequence is x m (n 1 )：
wherein ,am (n 1 ) Represents x m (n 1 ) Amplitude phi of phi m (n 1 ) Represents x m (n 1 ) N represents the code length;
and the optimization solving module is used for solving the optimization model by using a model solver to obtain the optimized phase encoding waveform with the code length.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the phase-encoding waveform group optimization design method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the phase-encoding waveform group optimization design method of any one of claims 1 to 7.
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