CN106526338A - Indoor ray tracing parameter correction method based on simulated annealing - Google Patents
Indoor ray tracing parameter correction method based on simulated annealing Download PDFInfo
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- CN106526338A CN106526338A CN201610911164.9A CN201610911164A CN106526338A CN 106526338 A CN106526338 A CN 106526338A CN 201610911164 A CN201610911164 A CN 201610911164A CN 106526338 A CN106526338 A CN 106526338A
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Abstract
The invention relates to the field intensity prediction technology based on indoor ray tracing, which adopts a simulated annealing algorithm as a parameter correction method for ray tracing. The optimal parameter of ray tracing at some special context is derived reversely according to a few actually-measured values. The technical scheme adopted by the invention is an indoor ray tracing parameter correction method based on simulated annealing. The method comprises the following steps of 1) scene selection, taking some indoor scene as an example, and actually measuring data of the scene; 2) parameter selection, wherein parameters used for correction are a reception sphere radius R, a wall dielectric constant [Epsilon]1, and a ground dielectric constant [Epsilon]2; 3) improvement of simulated annealing algorithm-adaptive search, using a simulated annealing method to calibrate ray tracing parameters, wherein the error of the search range, i.e., the disturbance interval is too large or too small, is reduced by a mode of adaptively adjusting the step length; and 4) parameter correction. The method provided by the invention is mainly applied to indoor field intensity prediction occasions.
Description
Technical field
The present invention relates to the field intensity prediction technology based on indoor ray trace, specifically, is related to the room based on simulated annealing
Inner rays tracking parameter bearing calibration.
Background technology
Compared to traditional statistical model, based on ray trace (Ray Tracing, RT) the channel mould that multipath electromagnetism is calculated
Type used as a kind of modal deterministic models, cover by the field intensity for being capable of accurately predicted city Microcell and indoor scene
Lid.However, ray tracing algorithm precision depends critically upon the parameter preset needed for algorithm.Parameter correcting method is intended to ask for being suitable for
In the optimum set of parameters of special scenes, so as to improve RT precision of predictions.
In geophysics and remote sensing fields, there is a class to be referred to as anti-using the method that radar return asks for medium electromagnetic parameter
Drill.As radar return cannot explicitly be expressed as the function of parameter, therefore carry out inverted parameters frequently with intelligent search algorithm.Inverting
Method has many kinds, including gradient method, Newton method, Monte Carlo method, genetic algorithm, simulated annealing (Simulated
Annealing, SA) algorithm etc..A kind of adaptive simulated annealing inversion method of step-size in search is proposed in document, compared to biography
System simulated annealing has higher search efficiency；Propose in document that the mixing that a kind of simulated annealing is combined with genetic algorithm is calculated
Method, can further improve local search ability on the premise of ability of searching optimum is ensured.
RT (ray trace) parameter corrections mathematically have uniformity, Gui Gen with geophysical parameter inversion problems
Knot bottom is all a kind of iteration optimal method to multi-targets function, and its Direct mapping relation mostly typically is implicit expression or more multiple
It is miscellaneous, it is difficult to use analytic method direct solution.Therefore RT (ray trace) ginsengs are solved by more ripe inverting and its improved method
Number Correction Problemss are feasible.Although document gives and enters line parameter school using simulated annealing to indoor ray tracing algorithm
Positive example, but improvement is not made in itself to searching algorithm.
The content of the invention
For overcoming the deficiencies in the prior art, it is contemplated that proposing the parameter using simulated annealing as ray trace
Bearing calibration, according to the anti-optimized parameter for releasing certain special scenes ray trace of a small amount of measured value such that it is able to carry out more smart
Accurate field intensity prediction.The technical solution used in the present invention is, based on the indoor ray trace parameter correcting method of simulated annealing, walks
It is rapid as follows：
1), choose scene
By taking certain indoor scene as an example, according to the scene measured data；
2), Selecting All Parameters
For correction parameter be：Receive radius of a ball R, metope permittivity ε1, ground permittivity ε2；
3), modified-immune algorithm adaptable search
Ray trace RT parameter correction is carried out using simulated annealing method, wherein, by the side of adaptive adjusting step
Formula disturbs the interval excessive too small error brought reducing hunting zone；
4), parameter correction
According to above-mentioned parameter selection method and search strategy modified-immune algorithm, calculated using improved simulated annealing
Method is corrected to indoor ray trace parameter.
Ray trace RT parameter correction is carried out using simulated annealing method to comprise the concrete steps that, if object function is
X={ x1,x2,x3... } and it is parameter set, make object function represent the mean square error of the measured value on sample reception point and RT predicted values
Difference, then object function expression formula is：
CiAnd MiThe field intensity calculated value being illustrated respectively at i-th receiving point and field intensity measured value, N are represented
Point total number.If XoptOptimized parameter to be solved is represented, then XoptMeet f (Xopt)=minf (X), is simulated annealing and realizes
Refutation process be iterative process, iteration is always carried out towards the direction for reducing object function, but is also allowed with certain probability
Receive the parameter set of " poor ", so as to the ability for possessing certain escape Local Extremum, the trip point probability of acceptance is used
Metroplise criterions are described：
Algorithm controls the carrying out of iteration by internal maximum iteration time n and external temperature T, and Δ f is the target after saltus step
The difference of functional value and functional value before, p is the trip point probability of acceptance, by Metroplise criterions judge decision iteration whether by
Receive.
Disturbance interval sets interval size in the following ways with representing, then：
δ in formulaiRepresent the interval initial range threshold value of disturbance, naFor the no received total degree of inner loop " saltus step ",
5.0 empiricals obtained for test of many times.
The characteristics of of the invention and beneficial effect are：
The invention provides a kind of bearing calibration of indoor ray trace field intensity prediction parameter, by an indoor scene reality
Example, 2.5GHz narrow band signals are surveyed and are emulated, according to a small amount of measured value on a certain path it is counter release 3 D ray with
The optimized parameter of track, successfully realizes parameter correction process, and predicting the outcome after correcting preferably can be coincide with measured value.
Description of the drawings：
Fig. 1 indoor scene model schematics.
Specific embodiment
A kind of improved simulated annealing method be present invention employs as RT (ray trace) parameter correcting method, can either
It is prevented effectively from and is absorbed in local minimum point, the iterations of positive algorithm can be reduced again as far as possible, efficiency of algorithm is improve.
Used as optimal method, simulated annealing possesses preferable global optimizing ability, in combinatorial optimization problem and company
It is widely used in continuous space optimization problem.If object function is y=f (X), X={ x1,x2,x3... it is parameter set, make target letter
Number represents the mean square error of the measured value on sample reception point and RT predicted values, then object function expression formula is：
CiAnd MiThe field intensity calculated value being illustrated respectively at i-th receiving point and field intensity measured value, N are represented
Point total number.If XoptOptimized parameter to be solved is represented, then XoptMeet f (Xopt)=minf (X).Ideally, with MiTable
The measured value for showing is may be considered in real parameter set XrealThe true field intensity of i-th receiving point under effect, then have Xopt→
Xreal；But actual conditions will consider the factors such as equipment precision, model of place precision, noise, actual parameter collection XrealCan not survey,
Therefore the X required byoptIt is to XrealPossibility predication, sometimes referred to as XoptFor " equivalent parameters ".The inverting realized with simulated annealing
Journey is actually iterative process, and on the whole, iteration is always carried out towards the direction for reducing object function, but is also allowed with one
Determine the parameter set that probability receives " poor ", so as to the ability for possessing certain escape Local Extremum.The trip point probability of acceptance is used
Metroplise criterions are described：
Algorithm controls the carrying out of iteration by internal global cycle frequency n and external temperature T, is sentenced by Metroplise criterions
It is disconnected to determine whether iteration is received.Initial distribution value X of X is set during beginning first0, one group of empirical value is usually taken, is calculated
Object function f (X).Then disturbance Δ X is taken in X each element neighbors arounds respectively constitute new parameter set X*=X+ Δ X are referred to as
For once " jumping ", new object function f (X are obtained*).Relatively f (X) and f (X*), if the latter is little compared with the former, i.e. object function
Diminished due to " jump " of this subparameter, illustrate that current " jump " is successful, then just receive current jump, even X
=X*, then proceed to start new " jump "；If the latter is big compared with the former, the current new X for producing just is illustrated*Mesh can not made
Scalar functions reduce, then just calculate Δ f=f (X*)-f (X) and Probability p, current " jump " is received with Probability p, even X=
X*, such " jump ", though object function can be made to become big, it contributes to method and is unlikely to be absorbed in local pole in searching process
Value point.So iteration continues successively, and with the reduction of temperature T, jumping probability tends to minimum and makes algorithmic statement, until searching out
Optimal solution Xopt。
Simulated annealing should set different hunting zones for different parameters, and hunting zone is also known as " perturbing area
Between ".If interval too small, globe optimum may be ignored, cause result not to be optimum；If interval excessive, due to iteration time
Number excessively causes convergence rate slack-off or reduces optimization precision.
Therefore, on the basis of this algorithm, we are made to hunting zone (disturbance is interval) the excessive too small error brought
Improve.Reduce hunting zone (disturbance is interval) the excessive too small error brought by way of adaptive adjusting step.
Thus obtain enhanced simulated annealing.Indoor ray trace parameter is corrected using this improved method, implemented
It is as follows：
1), choose scene
By taking certain indoor scene as an example, according to the scene measured data, enter line parameter school using enhanced simulated annealing
Just.Antenna launches 2.5GHz narrow band signals, using (y=1.8m on software radio USRP equipment indoors a RX path；
X=2.8～10.3m；Z=1.5m) surveyed.Model of place schematic diagram as shown in figure 1,
2), Selecting All Parameters
Before correction parameter, need first to determine parameter set, that is, finding out affects larger parameter to field intensity prediction result.Adopt herein
RT (ray trace) algorithm receives the radius of a ball as one for independently writing ray tube ray tracing method (C# language realization)
Individual important parameter, for adjusting receiving point RX path quantity.In terms of electromagnetic parameter, pertinent literature passes through detailed field research,
It was found that the impact of dielectric constant is far above two other magnetic conductivity and electrical conductivity.Therefore, the parameter herein for correction is：
Receive radius of a ball R, metope permittivity ε1, ground permittivity ε2。
3), modified-immune algorithm adaptable search
Simulated annealing should set different hunting zones for different parameters, and hunting zone is also known as " perturbing area
Between ".If interval too small, globe optimum may be ignored, cause result not to be optimum；If interval excessive, due to iteration time
Number excessively causes convergence rate slack-off or reduces optimization precision.Therefore self-adaptative adjustment step-size in search is adopted here, when " jump "
Without received number of times it is more when, expand " disturbance interval " to facilitate global search.To i-th parameter, interval table is disturbed
Show, then set interval size in the following ways：
δ in formulaiRepresent the interval initial range threshold value of disturbance, n is inner loop total degree, naDo not have for inner loop " saltus step "
There are received total degree, 5.0 empiricals obtained for test of many times.For three parameters that this is tested, initial ranging area
Between be respectively R：0.01m～0.1m；ε1、ε2：1～15.
4), parameter correction
According to above-mentioned parameter selection method and search strategy modified-immune algorithm, calculated using improved simulated annealing
Method is corrected to indoor ray trace parameter, RT (ray trace) algorithms for adopting herein for independently write ray tube ray with
Track method (C# language realization).For indoor scene, initial solution is set based on experience value, releases certain according to a small amount of measured value is counter
The optimized parameter of special scenes ray trace, carries out complete parameter correction process using said method relatively time-consuming, when sharing
4h22min (calls 420 ray traces to calculate, lowers the temperature 28 times, inner loop 15 times).Meanwhile, in the same circumstances, carry out solid
Correction of the method adjustment simulated annealing of fixed step size and enumerative technique traversal parameter to indoor ray trace parameter is tested, respectively
Contrasted with the strategy of the adaptive searching step size for adopting herein, parameter correction result is to such as table 1.In table 1 correct before this
One be experiment in parameter set according to the empirical that experiment experience is obtained；The three of its excess-three Xiang Weiben experiment employing
Plant methods experiment contrast.As can be seen from the table, according to enumerating the +/- fixed constant of decree parameter to travel through parameter, such as R with
+ 0.0025 from 0.01 is incremented to 0.1, ε1、ε215 are incremented to+1 from 3, then 18 × 13 × 13=3042 time RT need to be called altogether (to penetrate
Line is tracked) computing module, computing excessively takes and search precision is not as good as SA (simulated annealing) algorithm, therefore simulated annealing will
Far superior to enumerative technique；In simulated annealing, we have the simulated annealing of the fixed step size for employing general and sheet
The simulated annealing of the improved adaptive step of text, from table 1 it follows that compared with fixed step size, searched using self adaptation
The strategy of Suo Buchang, when initial interval sufficiently wide abundant, can effectively reduce the region of search, and in table, experimental data shows, calls
RT (ray trace) computing module number of times is identical, but the mean square error (er) of the SA of adaptive step (simulated annealing) algorithm is little
In the mean square error (er) of SA (simulated annealing) algorithm of fixed step size, it can be seen that the improved adaptive steps of this paper
SA (simulated annealing) algorithm improves search precision to a certain extent.
1 parameter correction result of table
The foregoing is only presently preferred embodiments of the present invention, not to limit the present invention, all spirit in the present invention and
Within principle, any modification, equivalent substitution and improvements made etc. should be included within the scope of the present invention.
Claims (3)
1. a kind of indoor ray trace parameter correcting method based on simulated annealing, is characterized in that, step is as follows：
1), choose scene
By taking certain indoor scene as an example, according to the scene measured data；
2), Selecting All Parameters
For correction parameter be：Receive radius of a ball R, metope permittivity ε1, ground permittivity ε2；
3), modified-immune algorithm adaptable search
Ray trace RT parameter correction is carried out using simulated annealing method, wherein, by way of adaptive adjusting step come
Reduce hunting zone and disturb the interval excessive too small error brought；
4), parameter correction
According to above-mentioned parameter selection method and search strategy modified-immune algorithm, using enhanced simulated annealing pair
Indoor ray trace parameter is corrected.
2. the indoor ray trace parameter correcting method based on simulated annealing as claimed in claim 1, is characterized in that, using mould
Plan method for annealing carries out ray trace RT parameter correction and comprises the concrete steps that, if object function is y=f (X), X={ x1,x2,
x3... } and it is parameter set, make object function represent the mean square error of the measured value on sample reception point and RT predicted values, then target
Function expression is：
CiAnd MiThe field intensity calculated value being illustrated respectively at i-th receiving point and field intensity measured value, N represent that receiving point is total on path
Number.If XoptOptimized parameter to be solved is represented, then XoptMeet f (Xopt)=min f (X), is simulated the anti-of annealing realization
Process i.e. iterative process is drilled, iteration is always carried out towards the direction for reducing object function, but also allow to receive with certain probability
The parameter set of " poor ", so as to the ability for possessing certain escape Local Extremum, trip point probability of acceptance Metroplise
Criterion is described：
Algorithm controls the carrying out of iteration by internal maximum iteration time n and external temperature T, and Δ f is the object function after saltus step
The difference of value and before functional value, p are the trip point probability of acceptance, judge to determine whether iteration is connect by Metroplise criterions
Receive.
3. the indoor ray trace parameter correcting method based on simulated annealing as claimed in claim 1, is characterized in that, perturbing area
Between with representing, then set interval size in the following ways：
δ in formulaiRepresent the interval initial range threshold value of disturbance, n is inner loop total degree, naFor inner loop " saltus step " not by
The total degree of acceptance, 5.0 empiricals obtained for test of many times.
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