CN108614242A - A kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion - Google Patents
A kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion Download PDFInfo
- Publication number
- CN108614242A CN108614242A CN201810248924.1A CN201810248924A CN108614242A CN 108614242 A CN108614242 A CN 108614242A CN 201810248924 A CN201810248924 A CN 201810248924A CN 108614242 A CN108614242 A CN 108614242A
- Authority
- CN
- China
- Prior art keywords
- ant
- lion
- radar
- ant lion
- optimization
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
- G01S7/28—Details of pulse systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
- G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/18—Phase-modulated carrier systems, i.e. using phase-shift keying
- H04L27/20—Modulator circuits; Transmitter circuits
Abstract
The present invention relates to a kind of radar-communication integration waveform design methods based on the optimization of multiple target ant lion, including：Establish radar-communication integration Waveform Design fitness function；Ant population and ant lion population are initialized, determines multiple target ant lion Optimized Iterative number；Initialize each ant fitness value, initialization elite ant lion position；Update ant position；Calculate ant fitness value in population；Space is updated storage, to exceeding storage space volume the case where is handled；Update ant lion position and elite ant lion position；Judge whether that reach multiple target ant lion Optimized Iterative number stops search if reaching, randomly chooses one group of Pareto optimal solution as integrated waveform parameter；Otherwise it repeats.The present invention considers blind area range and the rate of information throughput in integrated waveform application, it more disclosure satisfy that actual requirement of engineering, there are ant lion and elite ant lion to instruct jointly in ant evolutionary process, effectively avoid being absorbed in local optimum in searching process, improves convergence accuracy.
Description
Technical field
The present invention relates to a kind of radar-communication integration waveform design methods, especially a kind of to be optimized based on multiple target ant lion
Radar-communication integration waveform design method, belong to radar and wireless communication technology field.
Background technology
In modern operation system, various radar communication electronic apparatus applications are more and more extensive, largely improve
The fight capability of platform, but it is complicated due to electronic equipment, cause systems bulky, energy consumption increases and Electro Magnetic Compatibility is disliked
The problems such as change.In order to solve these problems, comprehensive radar-communication integration system (Integrated radar can be built
And communication system, IRCS), radar and communications equipment is organically combined, to reduce each class of electronic devices
Use.Radar and communication system, which are combined, can give full play to respective advantage, make up respective deficiency, greatly improve and be
System fullfledged combat capability.Radar and communications system is made of on constituting transmitter, receiver and antenna etc., for being total to for hardware
It enjoys and provides possibility.On this basis, in order to realize radar-communication integration, it is also necessary to solve integral system and use letter
Number Waveform Design problem, the research for the problem is also one of the hot issue studied at present.
Liu Shaohua proposes a kind of based on most for 2014 in " design of the radar-communication integration signal based on spread spectrum "
The radar-communication integration signal of small frequency shift keying (Minimum-Shift Keying, MSK) Direct Sequence Spread Spectrum, this method from
Signal of communication sets out, and being improved to signal of communication makes it meet the needs of radar system.Specifically to the digital base in communication
Band signal is spread, and good autocorrelation is made it have, to meet the requirement of radar data reduction；Then MSK is utilized
Technology is modulated signal, greatly improves the availability of frequency spectrum of system.The integration signal of this method design, due to using
Direct sequence spread spectrum skill, therefore the synchronization of pseudo noise code must be completed when being communicated, so that receiver docking is collected mail number
Carry out coherently despreading.With the lengthening of pseudorandom code word, it is desirable that synchronization accuracy improve, required synchronization time increases, in reality
The communication performance of integrated waveform is affected in engineer application.
Radar-communication integration Waveform Design needs while taking into account the performance of radar and communication system, is one sufficiently complex
Practical Project problem, this is also the key point of integrated Waveform Design.Orthogonal frequency division multiplexing (Orthogonal is used herein
Frequency Division Multiplexing, OFDM) the modulated signal of communication realization radar-communication integration wave of technology
Shape design selects blind area range to weigh radar performance, and the rate of information throughput weighs communication performance, then using the two structure one
Change the combined optimization function of waveform.Joint optimizing is carried out for both radar and the validity function of communication system, is had at present
Many Multipurpose Optimal Methods may be implemented, for example, multi-objective particle swarm optimization (Multi-objective particle
Swarm optimization, MOPSO) and Evolutionary multiobjective optimization (Evolutionary multi-objective
Optimization, EMO) etc..In the above method, since particle (or individual) lacks guidance in searching process, it is easily trapped into
Local optimum, it is difficult to accurately find radar and communication performance while reaching maximum integrated waveform parameter.
Invention content
For the above-mentioned prior art, the technical problem to be solved in the present invention is to provide one kind can avoid being absorbed in local optimum,
It can accurately search out radar and integrated waveform parameter that communication performance is optimal is optimized based on multiple target ant lion
Radar-communication integration waveform design method.
In order to solve the above technical problems, a kind of radar-communication integration waveform based on the optimization of multiple target ant lion of the present invention is set
Meter method, includes the following steps：
Step 1：Establish the fitness function of radar-communication integration Waveform Design；
Step 2：Ant population and ant lion population are initialized, determines the iterations of multiple target ant lion optimization；
Step 3：Initialize the fitness value of each ant, initialization elite ant lion position；
Step 4：Update the position of ant；
Step 5：Calculate the fitness value of ant in population；
Step 6：Update storage space, and to exceeding storage space volume the case where is handled；
Step 7：Update the position of the position and elite ant lion of ant lion；
Step 8：Judge whether that the iterations for reaching the optimization of multiple target ant lion stop search if reaching, it is random to select
One group of Pareto optimal solution is selected as integrated waveform parameter；Otherwise step 4 is repeated to step 8.
The present invention it is a kind of based on multiple target ant lion optimization radar-communication integration waveform design method, further include：
1. step 1 establishes the fitness function of radar-communication integration Waveform Design, include the following steps：
S1：Determine blind area range function R when integration waveform is applied in the form of radar signalbz：
An OFDM symbol in radar-communication integration signal is determined according to orthogonal frequency division multiplexi
Length Ts, TsMeet：Ts=Tg+ T, wherein TgFor the length of cyclic prefix, T is the basic symbol duration；
Obtain the bandwidth B of radar-communication integration signals, BsMeet：Bs=NcΔ f, wherein NcFor sub-carrier number, Δ f is
Subcarrier spacing, Δ f meet：
According to pulse duration TpDetermine the blind area range function R of radarbz, RbzMeet：
Wherein, TpMeet：Tp=Ts×Ns, NsFor TpThe number of interior OFDM symbol, TrTo use orthogonal frequency
The pulse repetition period of the integrated waveform of multiplexing technology, TrMeet：Wherein frFor pulse recurrence frequency；c0It is electromagnetism
The spread speed of wave is 3 × 108m/s；The duty ratio D of radar-communication integration signal meets：Wherein, D0For
Radar signal maximum duty cycle；
S2：Determine rate of information throughput R when integration waveform is applied in the form of signal of communicationb：
The modulation system of communication data is modulated using quadrature phase shift keying, the rate of information throughput R of databFor：
Wherein, T0Indicate time, T used in transmission 1bit data0Meet：Wherein, TOFDM1For
Using the time of one OFDM symbol of integrated waveform transfer of orthogonal frequency division multiplexi, TOFDM1Meet：
S3：Determine the fitness function of radar-communication integration Waveform Design：
Combined optimization function is built, the fitness function of optimizing is carried out as multiple target ant lion optimization method, obtains one
Change Waveform Design fitness function be：
Minimize：F (x)={ f1(x),f2(x)}
Wherein, x represents the vector of the influence factor composition of integrated waveform, x=[Ns,Nc,Tg,Δf,fr], multiple target ant
Lion optimizes to fitness function optimizing, f1(x) be radar blind area range function Rbz, f2(x) it is the rate of information throughput R communicatedb
Opposite number, i.e.-Rb。
2. step 2 initializes ant population and ant lion population, determine that the iterations of multiple target ant lion optimization are specially：
In Ns,Nc,Tg,Δf,frAnt position x is generated in given range at randomi=[xi1,xi2,xi3,xi4,xi5], xmax≤
xi≤xmin, i=1,2 ..., N, N is ant Population Size, xmaxRespectively to tie up the maximum value of parameter, x in ant positionminFor ant
The minimum value of parameter is respectively tieed up in position；
In Ns,Nc,Tg,Δf,frAnt lion position x is generated in given range at randomj=[xj1,xj2,xj3,xj4,xj5], j=1,
2 ..., N, N are ant lion Population Size, xmax≤xj≤xmin, xmaxRespectively to tie up the maximum value of parameter, x in ant lion positionminFor ant lion
The minimum value of parameter is respectively tieed up in position；
The iterations of multiple target ant lion optimization are set as Tmax。
3. step 3 initializes the fitness value of each ant, initialization elite ant lion position is specially：
According to the fitness function determined in step 1, the fitness value of each ant in ant population, initialization are calculated
The position of first ant in ant population is chosen as elite ant lion position in elite ant lion position.
4. step 4 updates the position of ant, including：
Random walk to ant in search space is normalized：
Wherein,It is i-th of variate-value of the t times iteration,It is the minimum value of i-th of variable of the t times iteration,It is
The maximum value of i-th of variable of the t times iteration, aiIt is the minimum value of i-th of variable random walk, biIt is that i-th of variable is swum at random
The maximum value walked；
Ant surrounds the random walk of ant lion, is influenced, is expressed as by ant lion trap：
Wherein, ctIt is the minimum value of all variables in the t times iteration, dtIt is the maximum value of all variables in the t times iteration；It is the minimum value of j-th of ant all variables in the t times iteration,It is j-th of ant all variables in the t times iteration
Maximum value；It is position of the corresponding ant lion of jth ant in the t times iteration；
Ant walks in trap, and due to the purpose that ant lion preys on ant, structure trap is back taper, ant meeting
It slides, is represented by trap bottom：
Wherein, I is the ratio that ant slides downwards,T is current iteration number, TmaxIt is greatest iteration
Number, w are the constants that t is determined, as t ＞ 0.1TmaxWhen, w=2；As t ＞ 0.5TmaxWhen, w=3；As t ＞ 0.75TmaxWhen, w
=4；As t ＞ 0.9TmaxWhen, w=5；As t ＞ 0.95TmaxWhen, w=6；
Ant is identical as the above-mentioned random walk around ant lion around the random walk of elite ant lion；
The random walk of ant when the t times iteration is usedIt indicates, ant is around elite ant lion random row when the t time iteration
Walk useIt indicates, then position of i-th ant in t+1 iteration is：
WhenConstraint processing is carried out to ant position, process is：It selects duty ratio D for constraints, controls
Ns,Nc,Tg, Δ f is constant, takes
5. the fitness value that step 5 calculates ant in population is specially：
Using step 1 fitness function, the fitness value of each ant in population is calculated.
6. step 6 updates storage space, and to exceeding storage space volume the case where is handled, and is included the following steps：
S1：The fitness value splicing of fitness value and ant population of new generation in memory space is lined up, is stored
Spatial adaptation angle value matrix is F_Save, and the fitness value matrix of ant population of new generation is F_Ant, the adaptation after splicing arrangement
Angle value matrix is F_Array, then F_Array=[F_Save, F_Ant]；
S2：The number of Pareto optimal solution in comparison statistics F_Array, and by the corresponding ant position of Pareto optimal solution
It picks out and constitutes new memory space；
S3：The case where to exceeding storage space volume, is handled, specially：
When memory space has been expired, the ant location information with most adjacent ant numbers in memory space is moved
It removes, the probability of removal is：Wherein, c is a constant more than 1, NiIt is phase around i-th of ant in memory space
The number of adjacent ant.
7. the position of step 7 update ant lion and the position of elite ant lion are specially：
The position for updating ant lion, when ant position is better than ant lion position, it is new that ant lion is moved to ant position structure
Trap, i.e.,：
Wherein,The position of jth ant lion when being the t times iteration,I-th ant when being the t times iteration
Position；
The position for updating elite ant lion, randomly selects one group of Pareto optimal solution, as elite ant lion from memory space
Position.
Beneficial effects of the present invention：The present invention initially sets up the model to be optimized of radar-communication integration Waveform Design；So
Multiple target ant lion optimization method is used afterwards, and optimizing is carried out to its parameter；Optimal integrated waveform parameter is finally obtained, using more
Target ant lion optimizes (Multi-objective ant lion optimizer, MOALO) method, and this method is simulated ant lion and captured
The nature process of ant instructs the evolution of ant by ant lion and elite ant lion, can avoid it and is absorbed in local optimum, Neng Gouzhun
The true integrated waveform parameter for searching out radar and communication performance is optimal.
The present invention has considered the information of the blind area range and communication aspects in terms of radar in integrated waveform application
Transmission rate, obtained integration waveform parameter more disclosure satisfy that the needs of Practical Project.
Compared to existing Multipurpose Optimal Method, the multiple target ant lion optimization method that the present invention uses is evolved in ant
There are both ant lion and elite ant lion to instruct jointly in the process, it is possible to prevente effectively from being absorbed in local optimum in searching process, improves and receive
The accuracy held back.
Description of the drawings
Fig. 1 is that a kind of flow of the radar-communication integration waveform design method based on the optimization of multiple target ant lion of the present invention is shown
It is intended to.
Fig. 2 is the effect of optimization comparison diagram of multiple target ant lion optimization and multi-objective particle swarm optimization.
Specific implementation mode
The present invention is further described in detail in the following with reference to the drawings and specific embodiments：
The present invention provides a kind of radar-communication integration waveform design method optimized based on multiple target ant lion, flow signal
Figure is as shown in Figure 1, include the following steps：
Step 1：Establish the fitness function of radar-communication integration Waveform Design.
Radar-communication integration signal uses OFDM technology, and an OFDM symbol in signal is determined first according to OFDM technology
Length be Ts=Tg+ T, TgFor the length of cyclic prefix, T is the basic symbol duration.It can obtain subcarrier spacingSub-carrier number is Nc, then the bandwidth of integration signal is Bs=NcΔf.The communication information included in OFDM symbol,
Radar signal needs exist with impulse form, therefore there are pulse durations and pulse recurrence frequency within a pulse period
Two concepts.Pulse duration Tp=Ts×Ns, wherein NsFor the number of OFDM symbol in a radar pulse, pulse repeats
Frequency (PRF) is fr。
For radar system, crucial performance indicator selects blind area range.In radar application, the blind area range of radar is
It is determined, can be obtained by the pulse duration:
Wherein, c0It is electromagnetic wave propagation speed, is 3 × 108m/s.Consider that radar signal is deposited in the form of discrete pulses
The duty ratio of signal is being required, radar signal maximum duty cycle D0, then
For communication system, the transmission rate of information is to weigh a key index of system performance.The tune of communication data
System is modulated using quadrature phase shift keying (QPSK), then the transmission rate of data is
Wherein, T0Indicate the time used in transmission 1bit data, for the integrated waveform using OFDM technology, pulse repeats
Period isWherein include NsA OFDM symbol, then transmit an OFDM symbol used time beBy NcHeight
Carrier wave is transmitted, then transmits the 1bit data used times and be:
For radar system, blind area range is smaller, and the radar performance of integrated waveform is better；And for communication system
System, the rate of information throughput is faster, and the communication performance of integrated waveform is better.It can thus be seen that radar-communication integration waveform
Design belongs to multi-objective optimization question, it is therefore an objective to search out while meet blind area range smaller faster with the rate of information throughput one
Body waveform parameter.The combined optimization function for building radar-communication integration waveform design method optimizes as multiple target ant lion
Method carries out the fitness function of optimizing, and the fitness function for obtaining integrated Waveform Design is：
Minimize：F (x)={ f1(x),f2(x)}
Wherein, x represents the vector of the influence factor composition of integrated waveform, x=[Ns,Nc,Tg,Δf,fr].Multiple target ant
Lion optimizes to fitness function optimizing, f1(x) be radar blind area range function i.e. Rbz, f2(x) it is the information transmission speed communicated
The opposite number of rate is-Rb。
Step 2：Ant population and ant lion population are initialized, determines the iterations of multiple target ant lion optimization.
Generate ant position x at random in each parameter given rangei=[xi1,xi2,xi3,xi4,xi5], xmax≤xi≤xmin,
I=1,2 ..., N, N are ant Population Size, xmaxRespectively to tie up the maximum value of parameter, x in ant positionminIt is each in ant position
Tie up the minimum value of parameter.
The iterations of multiple target ant lion optimization are set as Tmax, which can be as the end condition of search.
Step 3：Initialize the fitness value of each ant, initialization elite ant lion position.
According to the fitness function determined in step 1, the fitness value of each ant in ant population is calculated.Initialization essence
The position of first ant in ant population is chosen as elite ant lion position in English ant lion position.
Step 4：Update the position of ant.
The change of ant position is mainly influenced by two aspect factors, and first is that ant falls into ant lion trap, random row
Walking is influenced by ant lion trap；Second is that the walking of ant is instructed by elite ant lion, and elite ant lion instructs ant to search
The better region movement in position in space.
Ant prevents it from exceeding boundary in search space random walk, it should the random walk of ant is normalized,
Wherein,It is i-th of variate-value of the t times iteration,It is the minimum value of i-th of variable of the t times iteration,It is
The maximum value of i-th of variable of the t times iteration, aiIt is the minimum value of i-th of variable random walk, biIt is that i-th of variable is swum at random
The maximum value walked.
The random walk of ant is influenced by ant lion trap, is represented by：
Wherein, ctIt is the minimum value of all variables in the t times iteration, dtIt is the maximum value of all variables in the t times iteration；It is the minimum value of j-th of ant all variables in the t times iteration,It is j-th of ant all variables in the t times iteration
Maximum value；It is position of the corresponding ant lion of jth ant in the t times iteration.
Ant walks in trap, and due to the purpose that ant lion preys on ant, structure trap is back taper, ant meeting
It slides, is represented by trap bottom：
Wherein, I is the ratio that ant slides downwards,T is current iteration number, and T is maximum iteration,
W is the constant that t is determined.As t ＞ 0.1T, w=2；As t ＞ 0.5T, w=3；As t ＞ 0.75T, w=4；As t ＞
When 0.9T, w=5；As t ＞ 0.95T, w=6.
The walking of ant is also instructed by elite ant lion, and the random walk of elite ant lion is surrounded, and ant lion is surrounded with above-mentioned
Random walk it is identical.The random walk of ant when the t times iteration is usedIt indicates, ant is around elite ant when the t time iteration
Lion random walk is usedIt indicates, then position of i-th ant in t+1 iteration is
Ant position other than considering without departing from search space, also needs to carry out constraint processing in the updating.Constraints is selected
Duty ratio is selected, when duty ratio is unsatisfactory for demand, constraint processing is carried out to it.The method that processing uses is constrained to control remaining
Variable is constant, takesParameter value is limited on boundary.
Step 5：Calculate the fitness value of ant in population.
Using fitness function, the fitness value of each ant in population is calculated, the step is primarily in next step to depositing
Storage space is updated.
Step 6：Update storage space, and to exceeding storage space volume the case where is handled.
The forward position memory space, that is, Pareto (Pareto), is the set of Pareto (Pareto) optimal solution, for storing
The corresponding ant position of Pareto optimal solutions and fitness value, updated every time in iterative process ant position and fitness value it
After need to be updated memory space.
First, the fitness value splicing of fitness value and ant population of new generation in memory space is lined up.It deposits
Storage spatial adaptation angle value matrix is F_Save, and the fitness value matrix of ant population of new generation is F_Ant, suitable after splicing arrangement
Response value matrix is F_Array, then
F_Array=[F_Save, F_Ant]
Then, in comparison statistics F_Array Pareto optimal solutions number, and by Pareto optimal solutions corresponding ant position
It sets to pick out and constitutes new memory space.
Finally, to exceeding storage space volume the case where, is handled.The ant position stored in memory space is to select
Ant population in the optimal ant of fitness value, be because elite ant lion will generate out of memory space, therefore in order to avoid
The optimization of multiple target ant lion is absorbed in local optimum, when memory space has been expired, will have most adjacent ant numbers in memory space
Purpose ant location information removes, and the probability of removal is：Wherein, c is a constant more than 1, NiIt is memory space
In around i-th of ant adjacent ant number.
Step 7：Update the position of the position and elite ant lion of ant lion.
The position of ant lion is updated, after ant lion captures ant, ant lion can build trap, the update of ant lion position again
Principle is when ant position is better than ant lion position, and ant lion is moved to ant position and builds new trap, i.e.,
Wherein,The position of jth ant lion when being the t times iteration,I-th ant when being the t times iteration
Position.
The position of elite ant lion is updated, elite ant lion is randomly selected using roulette selection method from memory space
Pareto optimal solutions.
Step 8：Judge whether to meet termination criteria, if meeting standard, stop search, uses one group of roulette selection
Pareto optimal solutions are as integrated waveform parameter；Otherwise step 4 is repeated to step 8.
Further simulating, verifying is carried out to it in conjunction with Fig. 1：
1. experiment scene
In IEEE802.11a, radio LAN system is directed to 5.15-5.25,5.25-5.35,5.725-5.825GHz
Signal in frequency range is divided into the radar C-band of remote control and director radar generally use.Select radar-communication integration signal
Centre frequency is 5.8GHz；The pulse recurrence frequency f of signalr≤10kHz；OFDM sub-carrier numbers Nc≤25；Subcarrier spacing
309.3kHz≤Δf≤350kHz；The length of one complete OFDM symbol is that the circulating prefix-length of 4 μ s, OFDM is necessarily less than
The length of complete OFDM symbol, so circulating prefix-length Tg≤4μs；Signal pulse width is less than 100 μ s, so OFDM symbol
Number Ns≤25。
2. experiment content is analyzed
Experiment one：The combined optimization function of radar-communication integration Waveform Design is sought using the optimization of multiple target ant lion
Excellent, iterations are set as 100 times, and ant Population Size is 100, storage space volume 50, signal maximum duty cycle D0For
30%.Use one Pareto optimal solution of roulette selection as integrated waveform parameter out of memory space after iteration.
The results are shown in Figure 2 for convergence, and the integrated waveform parameter of roulette selection is OFDM symbol number Ns=11, subcarrier
Number Nc=23, circulating prefix-length Tg=0.15 μ s, subcarrier spacing Δ f=350kHz, pulse recurrence frequency fr=8.37kHz.
Experiment two：Using combined optimization object function as fitness function, compare the optimization of multiple target ant lion and multi-target particle
The crowded variance (Crowding Variance, CV) of group optimizing method and operation time (Computational Time, CT),
And it compares it and restrains result.
The forward positions Pareto that MOALO and MOPSO optimizes integrated waveform structure fitness function are as shown in Figure 2.
In Fig. 2, closer to the upper left corner of coordinate system, communication information transmission rate is faster, and radar range blind area is smaller, represents integrated wave
The performance of shape is better.From figure 2 it can be seen that Pareto forward position of the forward positions Pareto of MOALO compared to MOPSO is closer to seat
Mark system upper left side, the i.e. effect of optimization of MOALO are more preferable.Two kinds of optimization methods optimize independent operating 30 times to fitness function and unite
Average result is counted, as shown in table 1, it can be seen that faster (CT values are small), distributivity is more preferable (CV values are small) for the arithmetic speed of MOALO.
Performance indicators of table 1 MOALO and MOPSO to fitness function optimizing
Claims (8)
1. a kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion, which is characterized in that including following
Step：
Step 1：Establish the fitness function of radar-communication integration Waveform Design；
Step 2：Ant population and ant lion population are initialized, determines the iterations of multiple target ant lion optimization；
Step 3：Initialize the fitness value of each ant, initialization elite ant lion position；
Step 4：Update the position of ant；
Step 5：Calculate the fitness value of ant in population；
Step 6：Update storage space, and to exceeding storage space volume the case where is handled；
Step 7：Update the position of the position and elite ant lion of ant lion；
Step 8：Judge whether that the iterations for reaching the optimization of multiple target ant lion stop search if reaching, random selection one
Group Pareto optimal solution is as integrated waveform parameter；Otherwise step 4 is repeated to step 8.
2. a kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion according to claim 1,
It is characterized in that：Step 1 establishes the fitness function of radar-communication integration Waveform Design, includes the following steps：
S1：Determine blind area range function R when integration waveform is applied in the form of radar signalbz：
The length of an OFDM symbol in radar-communication integration signal is determined according to orthogonal frequency division multiplexi
Ts, TsMeet：Ts=Tg+ T, wherein TgFor the length of cyclic prefix, T is the basic symbol duration；
Obtain the bandwidth B of radar-communication integration signals, BsMeet：Bs=NcΔ f, wherein NcFor sub-carrier number, Δ f is that son carries
Wave spacing, Δ f meet：
According to pulse duration TpDetermine the blind area range function R of radarbz, RbzMeet：
Wherein, TpMeet：Tp=Ts×Ns, NsFor TpThe number of interior OFDM symbol, TrTo use orthogonal frequency division multiplexing skill
The pulse repetition period of the integrated waveform of art, TrMeet：Wherein frFor pulse recurrence frequency；c0It is the biography of electromagnetic wave
Speed is broadcast, is 3 × 108m/s；The duty ratio D of radar-communication integration signal meets：Wherein, D0Believe for radar
Number maximum duty cycle；
S2：Determine rate of information throughput R when integration waveform is applied in the form of signal of communicationb：
The modulation system of communication data is modulated using quadrature phase shift keying, the rate of information throughput R of databFor：
Wherein, T0Indicate time, T used in transmission 1bit data0Meet：Wherein, TOFDM1To use
The time of one OFDM symbol of integrated waveform transfer of orthogonal frequency division multiplexi, TOFDM1Meet：
S3：Determine the fitness function of radar-communication integration Waveform Design：
Combined optimization function is built, the fitness function of optimizing is carried out as multiple target ant lion optimization method, obtains integrated wave
Shape design fitness function be：
Minimize：F (x)={ f1(x),f2(x)}
Wherein, x represents the vector of the influence factor composition of integrated waveform, x=[Ns,Nc,Tg,Δf,fr], multiple target ant lion is excellent
Change to fitness function optimizing, f1(x) be radar blind area range function Rbz, f2(x) it is the rate of information throughput R communicatedbPhase
Anti- number, i.e.-Rb。
3. a kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion according to claim 1,
It is characterized in that：The step 2 initialization ant population and ant lion population determine the iterations tool of multiple target ant lion optimization
Body is：
In Ns,Nc,Tg,Δf,frAnt position x is generated in given range at randomi=[xi1,xi2,xi3,xi4,xi5], xmax≤xi≤
xmin, i=1,2 ..., N, N is ant Population Size, xmaxRespectively to tie up the maximum value of parameter, x in ant positionminFor ant position
In respectively tie up the minimum value of parameter；
In Ns,Nc,Tg,Δf,frAnt lion position x is generated in given range at randomj=[xj1,xj2,xj3,xj4,xj5], j=1,
2 ..., N, N are ant lion Population Size, xmax≤xj≤xmin, xmaxRespectively to tie up the maximum value of parameter, x in ant lion positionminFor ant lion
The minimum value of parameter is respectively tieed up in position；
The iterations of multiple target ant lion optimization are set as Tmax。
4. a kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion according to claim 1,
It is characterized in that：Step 3 initializes the fitness value of each ant, and initialization elite ant lion position is specially：
According to the fitness function determined in step 1, the fitness value of each ant in ant population is calculated, elite is initialized
The position of first ant in ant population is chosen as elite ant lion position in ant lion position.
5. a kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion according to claim 1,
It is characterized in that：Step 4 updates the position of ant, including：
Random walk to ant in search space is normalized：
Wherein,It is i-th of variate-value of the t times iteration,It is the minimum value of i-th of variable of the t times iteration,It is the t times
The maximum value of i-th of variable of iteration, aiIt is the minimum value of i-th of variable random walk, biIt is i-th of variable random walk
Maximum value；
Ant surrounds the random walk of ant lion, is influenced, is expressed as by ant lion trap：
Wherein, ctIt is the minimum value of all variables in the t times iteration, dtIt is the maximum value of all variables in the t times iteration；It is
The minimum value of j-th of ant all variables in the t times iteration,It is that all variables are most in the t times iteration for j-th of ant
Big value；It is position of the corresponding ant lion of jth ant in the t times iteration；
Ant walks in trap, and due to the purpose that ant lion preys on ant, structure trap is back taper, and ant can be to falling into
Trap bottom slides, and is represented by：
Wherein, I is the ratio that ant slides downwards,T is current iteration number, TmaxIt is maximum iteration,
W is the constant that t is determined, as t ＞ 0.1TmaxWhen, w=2；As t ＞ 0.5TmaxWhen, w=3；As t ＞ 0.75TmaxWhen, w=4；When
T ＞ 0.9TmaxWhen, w=5；As t ＞ 0.95TmaxWhen, w=6；
Ant is identical as the above-mentioned random walk around ant lion around the random walk of elite ant lion；
The random walk of ant when the t times iteration is usedIt indicates, ant is around elite ant lion random walk use when the t time iterationIt indicates, then position of i-th ant in t+1 iteration is：
WhenConstraint processing is carried out to ant position, process is：It selects duty ratio D for constraints, controls Ns,
Nc,Tg, Δ f is constant, takes
6. a kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion according to claim 1,
It is characterized in that：The fitness value of ant is specially in step 5 calculating population：
Using step 1 fitness function, the fitness value of each ant in population is calculated.
7. a kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion according to claim 1,
It is characterized in that：Step 6 updates storage space, and to exceeding storage space volume the case where is handled, including following step
Suddenly：
S1：The fitness value splicing of fitness value and ant population of new generation in memory space is lined up, memory space
Fitness value matrix is F_Save, and the fitness value matrix of ant population of new generation is F_Ant, the fitness value after splicing arrangement
Matrix is F_Array, then F_Array=[F_Save, F_Ant]；
S2：The number of Pareto optimal solution in comparison statistics F_Array, and the corresponding ant position of Pareto optimal solution is selected
Out constitute new memory space；
S3：The case where to exceeding storage space volume, is handled, specially：
When memory space has been expired, the ant location information with most adjacent ant numbers in memory space is removed, is moved
The probability removed is：Wherein, c is a constant more than 1, NiIt is adjacent ant around i-th of ant in memory space
Number.
8. a kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion according to claim 1,
It is characterized in that：The position of step 7 update ant lion and the position of elite ant lion are specially：
The position for updating ant lion, when ant position is better than ant lion position, ant lion is moved to ant position and builds new fall into
Trap, i.e.,：
Wherein,The position of jth ant lion when being the t times iteration,The position of i-th ant when being the t times iteration；
The position for updating elite ant lion, randomly selects one group of Pareto optimal solution, the position as elite ant lion from memory space
It sets.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810248924.1A CN108614242B (en) | 2018-03-25 | 2018-03-25 | Radar communication integrated waveform design method based on multi-objective ant lion optimization |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810248924.1A CN108614242B (en) | 2018-03-25 | 2018-03-25 | Radar communication integrated waveform design method based on multi-objective ant lion optimization |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108614242A true CN108614242A (en) | 2018-10-02 |
| CN108614242B CN108614242B (en) | 2022-04-05 |
Family
ID=63658871
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810248924.1A Active CN108614242B (en) | 2018-03-25 | 2018-03-25 | Radar communication integrated waveform design method based on multi-objective ant lion optimization |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108614242B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112085318A (en) * | 2020-07-28 | 2020-12-15 | 河南科技大学 | Client demand modular process configuration method based on multi-target ant lion algorithm |
| CN112763985A (en) * | 2020-12-25 | 2021-05-07 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Pulse Doppler radar sounding integrated waveform design method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107274038A (en) * | 2017-07-31 | 2017-10-20 | 上海电力学院 | A kind of LSSVM Prediction of annual electricity consumption methods optimized based on ant lion |
| CN107766991A (en) * | 2017-11-10 | 2018-03-06 | 国网浙江省电力公司电力科学研究院 | A kind of plan optimization method and system of distributed power source access power distribution network |
-
2018
- 2018-03-25 CN CN201810248924.1A patent/CN108614242B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107274038A (en) * | 2017-07-31 | 2017-10-20 | 上海电力学院 | A kind of LSSVM Prediction of annual electricity consumption methods optimized based on ant lion |
| CN107766991A (en) * | 2017-11-10 | 2018-03-06 | 国网浙江省电力公司电力科学研究院 | A kind of plan optimization method and system of distributed power source access power distribution network |
Non-Patent Citations (5)
| Title |
|---|
| ABD EL-RAOUF A 等: "Effect of Antlion Optimized Facts to Enhance Three Phase Induction Motor Dynamic Performance", 《2017 NINETEENTH INTERNATIONAL MIDDLE-EAST POWER SYSTEMS CONFERENCE (MEPCON)》 * |
| MIRJALILI S: "Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems", 《APPLIED INTELLIGENCE》 * |
| SUBHASHINI KR 等: "Development of an Enhanced Ant Lion Optimization Algorithm and its Application in Antenna Array Synthesis", 《APPLIED SOFT COMPUTING》 * |
| 尚进 等: "Pareto最优稀疏频率雷达波形设计", 《系统工程与电子技术》 * |
| 陈小红: "基于进化算法的高维多目标优化问题求解方法及应用", 《中国博士学位论文全文数据库 信息科技辑》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112085318A (en) * | 2020-07-28 | 2020-12-15 | 河南科技大学 | Client demand modular process configuration method based on multi-target ant lion algorithm |
| CN112085318B (en) * | 2020-07-28 | 2023-08-04 | 河南科技大学 | Client demand modularization process configuration method based on multi-target ant lion algorithm |
| CN112763985A (en) * | 2020-12-25 | 2021-05-07 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Pulse Doppler radar sounding integrated waveform design method |
| CN112763985B (en) * | 2020-12-25 | 2023-07-14 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Pulse Doppler radar sounding integrated waveform design method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108614242B (en) | 2022-04-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106685441B (en) | A kind of radio frequency stealth radar networking power distribution method based on cooperative game | |
| CN102546059B (en) | Non-supervision clustering-based distributed cooperative spectrum sensing method for cognitive self-organizing network | |
| Yu et al. | Cloud-orchestrated physical topology discovery of large-scale IoT systems using UAVs | |
| Ustebay et al. | Greedy gossip with eavesdropping | |
| CN104185272A (en) | WSN location method based on WSDV-Hop (Weighted and Selected DV-Hop) | |
| Zickler et al. | RSS-based relative localization and tethering for moving robots in unknown environments | |
| CN108508411A (en) | Passive radar external sort algorithm signal recognition method based on transfer learning | |
| CN107942310B (en) | The resource joint optimization method of distributed MIMO radar system multiple target location estimation | |
| CN108614242A (en) | A kind of radar-communication integration waveform design method based on the optimization of multiple target ant lion | |
| CN111628855A (en) | Industrial 5G dynamic multi-priority multi-access method based on deep reinforcement learning | |
| Kim et al. | Mean-field game theoretic edge caching in ultra-dense networks | |
| CN113382381B (en) | Unmanned aerial vehicle cluster network intelligent frequency hopping method based on Bayesian Q learning | |
| CN105117769A (en) | Identification method of deception jamming on the basis of differential evolution wolf pack algorithm | |
| CN104656070A (en) | Method for eliminating false target under radar networking | |
| Zhao et al. | Network formation games for the link selection of cooperative localization in wireless networks | |
| Ghanem et al. | Particle swarm optimization approaches for primary user emulation attack detection and localization in cognitive radio networks | |
| Demetri et al. | LaPS: LiDAR-assisted placement of wireless sensor networks in forests | |
| Zhuang et al. | GA-MADDPG: A Demand-Aware UAV Network Adaptation Method for Joint Communication and Positioning in Emergency Scenarios | |
| CN113766600B (en) | Mobile target positioning method of multi-base station wireless sensor network | |
| CN105376846B (en) | A kind of LTE wireless resource allocation methods | |
| CN104517141B (en) | Radio frequency identification network topology method based on load balance Yu particle cluster algorithm | |
| CN114492849A (en) | Model updating method and device based on federal learning | |
| CN104678351A (en) | Algorithm of indoor positioning system based on ZigBee technique | |
| Lhazmir et al. | UAV for wireless power transfer in IoT networks: A GMDP approach | |
| CN108810986B (en) | Non-orthogonal access downlink transmission time optimization method based on depth certainty strategy gradient |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |