CN115524661A - Short wave time difference positioning method for joint optimization of height of ionized layer and target position - Google Patents
Short wave time difference positioning method for joint optimization of height of ionized layer and target position Download PDFInfo
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- CN115524661A CN115524661A CN202210972440.8A CN202210972440A CN115524661A CN 115524661 A CN115524661 A CN 115524661A CN 202210972440 A CN202210972440 A CN 202210972440A CN 115524661 A CN115524661 A CN 115524661A
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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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0246—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves involving frequency difference of arrival or Doppler measurements
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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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0278—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves involving statistical or probabilistic considerations
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Abstract
The invention belongs to the field of signal parameter measurement and estimation, and discloses a short wave time difference positioning method for ionosphere height and target position joint optimization, which comprises the steps of firstly establishing a short wave over-the-horizon time difference positioning model; then, a two-dimensional mutual fuzzy correlation algorithm is adopted for the received signals to obtain the time delay difference between any two receiving stations; then, when the height of a visual distance scene, namely an assumed ionization layer, is zero, a rough positioning result is obtained by utilizing a Chan algorithm; and finally, on the basis of the coarse positioning result, jointly optimizing the ionosphere height and the target position by utilizing a genetic algorithm to obtain an accurate positioning result. Compared with the prior art, the scheme provided by the invention can realize high-precision effective positioning without prior information related to the ionosphere parameters, and has the advantages of wide algorithm application range, strong robustness and simple implementation.
Description
Technical Field
The invention belongs to the field of signal parameter measurement and estimation, and particularly relates to a short-wave beyond visual range time difference positioning method based on ionization layer height and target position joint optimization.
Background
Short-wave communication is the only remote communication means without the restriction of network hubs and active relays, and the propagation distance can reach thousands of kilometers through a transmission mode of ionosphere reflection. The domestic and foreign scholars have partially studied on the aspect of short-wave over-the-horizon positioning, and the currently common positioning methods mainly comprise two types: based on a double-station/multi-station direction-finding intersection positioning technology and a single-station direction-finding positioning technology. The traditional double-station/multi-station direction-finding intersection positioning technology is based on an arrival angle positioning method, and the position of a radiation source is determined by intersection of two or more angle directions; the single-station direction-finding positioning technology realizes the positioning of a single receiving station by measuring the azimuth angle, the elevation angle and the ionospheric reflection height of the short-wave signals. Both methods need direction finding of incoming wave signals, but direction finding necessarily uses an antenna array, and compared with a microwave frequency band, a short wave array occupies a large area, and in order to realize high direction finding precision, the aperture of the array can reach hundreds of meters; and meanwhile, the equipment is complex, and the production and maintenance cost is high. Therefore, a time difference positioning method is adopted, and compared with the traditional direction finding positioning technology, the device is simple, the processing time is short, the cost is low, and the maneuverability is strong. The method comprises the steps that a small number of scholars in China and abroad establish a time difference positioning model to calculate the position of a target radiation source on the basis that the ionosphere height is known or the ionosphere height is calculated through some empirical information, the time difference positioning method needs to deeply understand the ionosphere characteristics, and meanwhile, a large amount of data accumulation is carried out on historical parameter information of the ionosphere in each region, and obviously, the time difference positioning method is not possible; meanwhile, the problem that the position accuracy is sharply reduced due to the fact that the calculated ionospheric height is not accurate exists.
Disclosure of Invention
The invention aims to provide a short-wave over-the-horizon time difference positioning method based on ionosphere height and target position joint optimization, and solves the problems that ionosphere reflection height is difficult to solve and positioning accuracy is limited due to inaccurate calculation results in the existing method.
The technical scheme adopted by the invention is as follows:
a short-wave time difference positioning method for ionospheric height and target position joint optimization specifically comprises the following steps:
step 1, constructing a short-wave over-the-horizon time difference positioning model, which specifically comprises the following steps:
in the short-wave signal over-the-horizon transmission model, the signal transmission distance from a target radiation source to each receiving station is represented as follows:
in the formula, N r Indicating the number of receiving stations, N r ≥4，h i Indicating the ionized layer reflection height in the ith path, d i The great circle distance between two points on the ground is represented by the spherical cosine formula (2),
and
representing the latitudinal coordinates of the target radiation source and the ith receiving station respectively;
let t 0 The target radiation source emits a signal at the moment, and the moment when the ith receiving station receives the signal is t i The time when the jth receiving station receives the signal is t j J ≠ i, then
In the formula, τ i And τ j Respectively correspondingly representing the time delay, V, corresponding to the ith path and the jth path c Making the ith path and the jth path correspond to each other for the propagation velocity of electromagnetic waveDelay difference Δ τ ij ＝τ i -τ j Then the equation for the time difference location is expressed as:
plus the earth surface equation:
consisting of the formulae (1), (4) and (5)
A multivariate nonlinear equation system of (1);
and 2, step: the time delay difference between any two receiving stations is solved by utilizing a two-dimensional mutual fuzzy correlation algorithm, which specifically comprises the following steps:
using two-dimensional mutual fuzzy formulas
Wherein, g i (t) and g j (t) correspond to the narrow-band signals received by the ith and jth receiving stations, respectively, Δ τ ij For the time delay difference of the two signals,
for Doppler frequency difference of two signals, the maximum value is searched in a two-dimensional fuzzy plane formed by a delay axis and a Doppler frequency axis together to obtain the delay difference delta tau between the two signals ij Difference of sum Doppler shift
And 3, step 3: the time delay difference delta tau obtained in the step 2 ij In formula (3), the ionospheric reflection height h is not considered i Fast food h i =0, then represented by the formulae (1), (3) and(4) Make up a unit only about
And solving to obtain a coarse positioning result of the target radiation source by utilizing a Chan algorithm in the traditional sight distance time difference positioning
And 4, randomly generating sample individuals to form an initialization population according to the coarse positioning result obtained in the step 3, and performing joint optimization on the target position and the ionospheric virtual height of each path by adopting a genetic algorithm to obtain the accurate position of the target radiation source.
Wherein, the step 4 comprises the following steps:
1) Selecting a coding strategy: determining parameters l and l to be optimized according to the coarse positioning result obtained in the step 3,
h i Selecting a binary coding mode to code each parameter to be estimated;
2) Defining a fitness function:
3) Randomly generating K samples to form an initialization population, wherein the K sample is expressed as
4) Calculating the fitness function value f (x) corresponding to each sample individual k ),k＝1,2,…,K；
5) Judging whether the population performance meets the maximum genetic iteration times or not, and if so, outputting the optimal parameters; otherwise, according to the genetic strategy, applying a selection operator, a crossover operator and a mutation operator to act on the population to generate a next generation population, and turning to the step 4).
The invention has the beneficial effects that:
1. compared with the traditional direction-finding positioning technology, the short-wave time difference positioning method has the advantages of simple equipment, short processing time, low cost and strong maneuverability.
2. The invention adopts the short wave over-the-horizon time difference positioning method based on the ionosphere height and target position joint optimization, does not need to estimate the ionosphere height in advance, and has wide application range and simple and effective algorithm.
Drawings
FIG. 1 is a schematic diagram of short wave signal propagation;
FIG. 2 is a short-wave signal over-the-horizon transmission model;
FIG. 3 is a flow chart for jointly optimizing a target position and an ionosphere height using a GA algorithm;
FIG. 4 is a graph showing the variation of the fitness function with genetic algebra and the variation of the average distance between two adjacent algebras with genetic algebra in the process of jointly estimating the target position and the ionosphere height by using the GA algorithm.
FIG. 5 is a graph of the variation of the positioning accuracy of the algorithm proposed by the present invention with the number of Monte Carlo simulations.
Detailed Description
The invention is further described with reference to the following detailed description and accompanying drawings.
The technical scheme adopted by the short-wave time difference positioning method for ionosphere height and target position joint optimization is that a short-wave beyond visual range time difference positioning model is established firstly; then, a two-dimensional mutual fuzzy correlation algorithm is used for solving the time delay difference between any two receiving stations; then, when the height of a visual distance scene, namely an assumed ionization layer, is zero, a rough positioning result is obtained by utilizing a Chan algorithm; and finally, on the basis of the coarse positioning result, jointly optimizing the ionosphere height and the target position by using a genetic algorithm to obtain an accurate positioning result. The method comprises the following specific steps:
step 1: building short wave over-the-horizon time difference positioning model
As shown in fig. 1, a short wave signal propagation diagram is shown, and the short wave signal is transmitted through ionospheric reflection. Obviously, in the time difference positioning method, besides the latitude and longitude of the radiation source, the ionospheric pseudo height of each path is also an important unknown parameter. As shown in FIG. 2, the short wave signal over-the-horizon propagation model can be approximated by the signal transmission distance from the target radiation source to each receiving station
In the formula, N r Indicating the number of receiving stations, N r ≥4，h i Is the ionization layer reflection height in the ith path, d i The great circle distance between two ground points is shown in (-) and can be obtained by the spherical cosine formula (2),
and
respectively representing the longitude and latitude coordinates of the target radiation source and the ith receiving station.
Let t 0 The target radiation source emits a signal at the moment, and the moment when the ith receiving station receives the signal is t i The time when the jth receiving station (j ≠ i) receives the signal is t j Is provided with
In the formula, τ i 、τ j Respectively representing the time delay, V, corresponding to the ith path and the jth path c Is the electromagnetic wave propagation velocity. Let Δ τ ij ＝τ i -τ j It is apparent that ij For the time delay difference corresponding to the ith path and the jth path, the equation of time difference positioning can be expressed as
In addition to the equation for the surface of the earth,
consisting of the formulae (1), (4) and (5)
A multivariate nonlinear equation system.
Step 2: method for solving time delay difference between any two receiving stations by utilizing two-dimensional mutual fuzzy correlation algorithm
The two-dimensional cross-ambiguity correlation algorithm is adopted because when a short wave channel propagates signals, not only fluctuation of signal amplitude caused by fading exists, but also frequency drift of transmitted signals caused by Doppler effect exists in propagation; the doppler shift is caused by the frequent fast motion of the ionosphere and the fast change of the height of the reflector, which causes the length of the propagation path to change and the phase of the signal to change. This phase change can be seen as a doppler shift of the high frequency carrier caused by the irregular motion of the ionosphere.
Using two-dimensional mutual fuzzy formulas
Wherein, g i (t)、g j (t) is the narrow band signal received by the ith and jth receiving stations, Δ τ ij For the time delay difference of the two signals,
for the Doppler frequency difference of the two signals, the maximum value is searched in a two-dimensional fuzzy plane formed by the delay axis and the Doppler frequency axis together, so that the delay difference delta tau between the two signals can be obtained ij Difference of sum Doppler shift
And step 3: solving a coarse positioning result by utilizing a Chan algorithm under a visual range scene
The time delay difference delta tau obtained in the step 2 ij In formula (3), while not considering ionospheric reflection height h i Instant messenger h i =0, such that the composition of formula (1) (3) (4) is only about
The system of the binary equations utilizes the Chan algorithm in the traditional sight distance time difference positioning to solve the coarse positioning result of the target radiation source
And 4, step 4: method for realizing accurate positioning by jointly optimizing ionospheric height and target position by using genetic algorithm
And (3) randomly generating sample individuals to form an initialization population according to the coarse positioning result obtained in the step (3), and performing joint optimization on the target position and the ionospheric virtual height of each path by adopting a Genetic Algorithm (GA) to obtain the accurate position of the target radiation source. The specific process is shown in FIG. 3:
1) Selecting a coding strategy: determining parameters l and l to be optimized according to the coarse positioning result obtained in the step 3,
h i And (4) selecting a binary coding mode to code each parameter to be estimated.
2) Defining a fitness function:
3) Randomly generating K samples to form an initialization population, wherein the K sample can be expressed as
4) Calculating the fitness function value f (x) corresponding to each sample individual k ),k＝1,2,…,K。
5) Judging whether the group performance meets the optimization criterion: selecting the maximum genetic iteration number Iter _ max as an optimization criterion, outputting an optimal parameter if the maximum genetic iteration number Iter _ max is met, otherwise, generating a next generation group by using a selection operator, a crossover operator and a mutation operator according to a genetic strategy, and starting a new generation of heredity.
6) Turning to the step 4), calculating the fitness function value of each sample individual in the new population.
The following is a more specific example:
in the experiment, 4 short wave receiving stations are respectively positioned at Harbin, shunzhen, shanghai and Fujian, a radiation source is set to be positioned in Western Ann, and the large circle distance between each receiving station and the radiation source is 1900km \953km \\\\\\ 1240km \1385kmrespectively. In addition, the ionospheric reflection heights for the four paths are h 1 ＝180km，h 2 ＝320km，h 3 ＝265km，h 4 =230km. Calculating actual distances reflected by an ionosphere between the receiving station and the target to be 1934km, 1148km, 1349km and 1459km according to the formula (1), converting the distances into corresponding time delay values, and generating N through simulation r And the signal modulation type is BPSK, the carrier frequency of the signal is 13.2MHz, the bandwidth of the signal is 10KHz, the intermediate frequency sampling rate is 100KHz, the noise of the signal is white Gaussian noise, and the signal-to-noise ratio is 13=12dB. Adding Doppler shift to each short-wave signal simultaneously
Firstly, a two-dimensional cross-correlation algorithm is utilized to carry out time difference estimation on a received signal, and then a traditional line-of-sight time difference positioning Chan algorithm is utilized to obtain a coarse positioning result of a target radiation source
Then, the target position is jointly estimated by using the GA algorithm
And ionosphere height
Realizes accurate positioning, wherein the parameters l,
h i Has a value range of
h i ∈[100km,350km]The binary coding mode is selected, the coding length of l is 10,
has a code length of 10,h i The code length of (1) is 12, the maximum iteration number Iter _ max =600, the number of samples in the group is K =100, the selection operator adopts non-return type remainder random sampling, and the crossover operator adopts crossover probability P c =0.5, mutation operator adopts mutation probability P e And =0.08. Fig. 4 shows the variation of the fitness function with the genetic algebra and the variation of the average distance between two adjacent generations with the genetic algebra in the process of jointly estimating the target position and the ionospheric height by using the GA algorithm, and fig. 5 shows the variation of the positioning accuracy of the algorithm proposed by the present invention with the monte carlo simulation times.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, but any modifications or equivalent variations made according to the technical spirit of the present invention are within the scope of the present invention as claimed.
Claims (2)
1. A short-wave time difference positioning method for ionospheric height and target position joint optimization is characterized by specifically comprising the following steps:
step 1, constructing a short-wave beyond visual range time difference positioning model, which specifically comprises the following steps:
in the short-wave signal over-the-horizon transmission model, the signal transmission distance from a target radiation source to each receiving station is represented as follows:
in the formula, N r Indicating the number of receiving stations, N r ≥4，h i Indicating the ionospheric reflection height in the ith path, d i The great circle distance between two points on the ground is represented by the spherical cosine formula (2),
and
respectively representing longitude and latitude coordinates of a target radiation source and an ith receiving station;
let t 0 The time when the target radiation source emits a signal and the time when the ith receiving station receives the signal is t i The time when the jth receiving station receives the signal is t j J ≠ i, then
In the formula, τ i And τ j Respectively correspondingly representing the time delay, V, corresponding to the ith path and the jth path c For the propagation speed of the electromagnetic wave, the corresponding time delay difference delta tau of the ith path and the jth path is set ij ＝τ i -τ j Then the equation of the time difference location is expressed as：
Plus the earth surface equation:
consisting of the formulae (1), (4) and (5)
A multivariate nonlinear equation system of (2);
step 2: the time delay difference between any two receiving stations is obtained by utilizing a two-dimensional mutual fuzzy correlation algorithm, which specifically comprises the following steps:
using two-dimensional mutual fuzzy formulas
Wherein, g i (t) and g j (t) corresponds to the narrow-band signals received by the ith and jth receiving stations, respectively, Δ τ ij For the time delay difference of the two signals,
for the Doppler frequency difference of the two paths of signals, the maximum value is searched in a two-dimensional fuzzy plane formed by a delay axis and a Doppler frequency axis together, and the delay difference delta tau between the two paths of signals is obtained ij Difference of sum Doppler shift
And step 3: the time delay difference delta tau obtained in the step 2 ij Substitution into formula (3) without taking into consideration the ionospheric reflection height h i Instant messenger h i If =0, then the two formulae (1), (3) and (4) form a single gateIn that
And solving to obtain a coarse positioning result of the target radiation source by utilizing a Chan algorithm in the traditional sight distance time difference positioning
And 4, step 4: and (4) randomly generating sample individuals to form an initialization group according to the coarse positioning result obtained in the step (3), and performing joint optimization on the target position and the ionospheric virtual height of each path by adopting a genetic algorithm to obtain the accurate position of the target radiation source.
2. The ionospheric height and target position joint optimized short-wave time difference positioning method of claim 1, wherein the specific steps of step 4 are as follows:
1) Selecting a coding strategy: determining parameters l to be optimized according to the coarse positioning result obtained in the step 3,
h i Selecting a binary coding mode to code each parameter to be estimated;
2) Defining a fitness function:
3) Randomly generating K samples to form an initialization population, wherein the kth sample is expressed as
4) Calculating the fitness function value f (x) corresponding to each sample individual k ),k＝1,2,…,K；
5) Judging whether the population performance meets the maximum genetic iteration times or not, and if so, outputting an optimal parameter; otherwise, according to the genetic strategy, applying a selection operator, a crossover operator and a mutation operator to act on the population to generate a next generation population, and turning to the step 4).
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116593959A (en) * | 2023-05-17 | 2023-08-15 | 中国人民解放军战略支援部队航天工程大学 | Method and system for positioning radiation source by mutual ambiguity function mapping based on carrier frequency search |
| CN117706479A (en) * | 2023-12-12 | 2024-03-15 | 江苏君立华域信息安全技术股份有限公司 | Short wave time difference positioning method based on genetic algorithm optimization |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116593959A (en) * | 2023-05-17 | 2023-08-15 | 中国人民解放军战略支援部队航天工程大学 | Method and system for positioning radiation source by mutual ambiguity function mapping based on carrier frequency search |
| CN116593959B (en) * | 2023-05-17 | 2024-03-15 | 中国人民解放军战略支援部队航天工程大学 | Method and system for positioning radiation source by mutual ambiguity function mapping based on carrier frequency search |
| CN117706479A (en) * | 2023-12-12 | 2024-03-15 | 江苏君立华域信息安全技术股份有限公司 | Short wave time difference positioning method based on genetic algorithm optimization |
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