CN113534116A - Echo phase characteristic extraction method based on double-frequency transmitting signal - Google Patents
Echo phase characteristic extraction method based on double-frequency transmitting signal Download PDFInfo
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- CN113534116A CN113534116A CN202110600563.4A CN202110600563A CN113534116A CN 113534116 A CN113534116 A CN 113534116A CN 202110600563 A CN202110600563 A CN 202110600563A CN 113534116 A CN113534116 A CN 113534116A
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Abstract
The invention provides an echo phase characteristic extraction method based on a dual-frequency transmitting signal, which mainly aims at the problems of high false alarm rate and weak target identification capability of active target detection and provides an echo phase characteristic extraction method based on a dual-frequency transmitting signal. The invention has obvious difference in phase characteristic distribution extracted aiming at different types of targets, and can effectively represent the hard and soft properties of the surface medium of the underwater scatterer. Through simulation analysis and pool test verification, the phase characteristics of the extracted target can be used for judging the attributes of target materials, the identification accuracy and the identification tolerance under the actual environment can be improved, a target identification characteristic library is enriched, and a technical basis is provided for the development of low-frequency active target detection and identification equipment.
Description
Technical Field
The invention belongs to the field of sonar array signal processing, and mainly relates to an echo phase characteristic extraction method based on a dual-frequency transmitting signal.
Background
The current low-frequency active sonar detection and identification process generally has the outstanding problems of high target detection false alarm rate, weak target identification capability and the like, and researches on low-frequency acoustic feature extraction methods of active targets such as low-frequency elastic scattering features, macroscopic physical features, waveform structural features and the like of target echoes are urgently needed. The echo feature extraction research needs to fully consider the influence of environment uncertainty, target diversity, emission signal form and bandwidth on feature separability, and the extracted echo features are required to be slightly influenced by non-target factors such as environment and signals on one hand and to better reflect the essential attributes of the targets on the other hand. Great progress has been made at present for the explicit or implicit existence of elastic acoustic scattering characteristic information associated with physical properties of target materials, structures and the like in echoes, low-frequency echo envelope characteristic information associated with target geometric structures, target geometric scale estimation methods, target motion parameter estimation methods and the like. The invention develops the technical research of low-frequency scattering phase characteristic extraction on the basis of the research, seeks for physical characteristics with strong separability and good stability, and provides powerful physical clues for target identification.
Disclosure of Invention
The invention mainly aims at the problems of high false alarm rate and weak target identification capability of active target detection, provides an echo phase characteristic extraction method based on a dual-frequency emission signal, and provides technical support for low-frequency active target detection and identification.
The object of the present invention is achieved by the following technical means. An echo phase characteristic extraction method based on double-frequency emission signals comprises the following steps:
setting a transmitting signal:
and has the following components: omega2=μω1,
Then the reflected echo is
Where, phi is the phase jump caused by the target, phi is pi for a soft surface target, and phi is 0 for a hard surface target;
in order to estimate the value of phi, the target reflection echo is filtered through a band-pass filter to respectively obtain two wavelets:
for wavelet pR1Performing mu-fold frequency scale transformation, and then correlating with the wavelet pR2Conjugate multiplication is carried out to obtain:
The phase term 2 pi n mu in the formula is fuzzy phase caused by periodicity of complex exponential, and for discrete echo, the complex phase comparison sequence obtained by the above processingThe argument is (mu-1) phi +2 pi n mu, and for a given value of mu, the argument values for targets with different surface properties will be different.
The invention has the beneficial effects that: the invention has obvious difference in phase characteristic distribution extracted aiming at different types of targets, and can effectively represent the hard and soft properties of the surface medium of the underwater scatterer. Through simulation analysis and pool test verification, the phase characteristics of the extracted target can be used for judging the target material attribute, the identification accuracy and the identification tolerance under the actual environment can be improved, and a technical basis is provided for low-frequency active target detection and identification equipment.
Drawings
Fig. 1 is a schematic diagram of an active sonar target detection process;
FIG. 2 is a flow chart of a phase extraction process;
FIG. 3 is a schematic diagram of phase output characteristics of two types of targets in simulated echo;
FIG. 4 is a schematic diagram of phase output characteristics of two types of targets under the echo theory modeling;
FIG. 5 is a schematic diagram of the target phase output result obtained by the water pool test.
Detailed Description
The specific implementation of the algorithm is explained in detail below by theoretical derivation, simulation and pool testing, with reference to the accompanying drawings.
(1) Basic theory
In the active sonar target detection process, testConsider the following approximation: (1) the target surface is a planar boundary compared to the acoustic wavelength; (2) incident plane wave, let the incident wave be pincThe reflected echo is pR. Then there are:
pR=R·pinc (1)
wherein, R is the reflection coefficient of the target surface, and when the size of the target surface is far larger than the wavelength of the incident sound wave, the value of R is as follows:
as can be seen from the above formula, when the target reflecting surface is hard, ρ is satisfiedBcB-ρAcA>When the reflection coefficient is 0, the reflection coefficient is a positive value, the reflected wave is a copy of the incident wave weighted by the amplitude | R |, and when the target reflection surface is softer, the rho is satisfiedBcB-ρAcAWhen the amplitude is less than 0, the reflected wave has the weighting with the amplitude of | R |, and also has the phase jump of π, so that the phase jump of the transmitted wave relative to the incident wave has an indication effect on the hardness of the reflecting surface of the target, and the active sonar target detection process is as shown in FIG. 1.
For the actual marine environment, because the sea surface is a soft interface, the sound wave generates pi phase jump through one-time sea surface reflection, but the sound wave needs to be reflected through two-way sea surface or sea floor, the echo phase jump caused by the sea surface reflection is integral multiple of 2 pi, and meanwhile, because the sea floor is a hard boundary, the phase jump is not generated, so that the influence of the sea interface reflection can be ignored under the ideal condition, and the phase jump of the echo is mainly caused by target surface reflection.
Now consider the following transmit signals:
and has the following components: omega2=μω1,
Then the reflected echo is
Where phi is the phase jump caused by the target, phi-pi for a soft surface target and phi-0 for a hard surface target.
In order to estimate the value of phi, a band-pass filter is designed to filter the echo, and two wavelets are obtained respectively:
for wavelet pR1Performing mu-fold frequency scale transformation, and then correlating with the wavelet pR2Conjugate multiplication is carried out to obtain:
The phase term 2 pi n mu in the formula is fuzzy phase caused by periodicity of complex exponential, and for discrete echo, the complex phase comparison sequence obtained by the above processingThe argument is (mu-1) phi +2 pi n mu, and for a given value of mu, the argument values for targets with different surface properties will be different. For example, when taking μ ═ 3/2, the amplitude values for the hard surface target echoes are 0, ± pi, while for soft surfaces the values are pi/2, -pi/2 or 3 pi/2, the amplitude values of the phase comparison sequence for the reflected echoes of surface targets of different nature will be distributed over different angular regions without noise pollution.
A flow chart of the phase feature extraction algorithm is shown in fig. 2.
(2) Simulation analysis
Considering the similarity between the frequency spectrum structure of the comb spectrum and the target echo, firstly, a sinusoidal modulation Signal (SFM) is added with certain noise to simulate the echo of the target. Can be expressed as:
wherein f is0Is the center frequency of the signal, fmFor modulating frequency, beta is a modulation parameter, and the bandwidth of the signal is B ≈ 2fm(1+ β). The echo of an actual target is simulated by adding phase jump and Gaussian white noise to a double-frequency pulse signal, and the phase measurement method is verified. Designing the pulse width of the transmitted signal to be 100ms, f0=3000HZ,fm600hz, and optionally f1=f0-fm,f2=f0+fmThe two lines of spectrum estimate the echo phase. Thus, μ ═ f2/f 13/2, for hard surface target echoes, the phase outputs are mainly distributed around 0 and pi, and for soft surface echoes, the phase outputs should be distributed around pi/2 and 3 pi/2, according to the algorithm proposed herein, we simulate the phase outputs under different signal-to-noise ratios, as shown in the graphs of fig. 3. From the simulation result, the phase measurement method has better effect on identifying hard and soft targets.
In addition, the invention also simulates the phase output of the spherical shell with the absolutely hard and the absolutely soft surface in the free field according to the algorithm. And modeling the scattering echo by adopting a fluctuation theory, wherein the expression is as follows:
while designing the transmitted signal to be f1=1200,f2The echo phase output was estimated 1800 two line spectra and the simulation results are shown in figure 4.
As can be seen from simulation analysis, the phase jump of the echo can well realize the classification of hard targets and soft targets. The method provides a very effective feature extraction method for identifying objects such as soft fish swarms of metal objects in an underwater environment.
(3) Pool experiment data analysis
To verify the separability of this feature, we performed experiments on stainless steel and non-metallic balloon targets in a water bath.
The experimental conditions are as follows: the waveguide water pool is 14m long, 1.4m wide and 1.4m high, the silencing tiles are laid around the water pool, sand and stones are fully paved on the water bottom, the target depth is about 70cm, and the receiving array depth is about 70 cm. A high-frequency transmitting transducer with the transmitting bandwidth of 50-100KHz and a horizontal linear array receiving array with 16 array elements are adopted, and a signal generating and collecting device is used for transmitting two single-frequency signals and hyperbolic frequency modulation signals with the frequency band of 70-90 to respectively excite stainless steel and non-metal balloon targets. Firstly, the hyperbolic frequency modulation signal is used for determining the position of a target through a matched filtering algorithm, and then two single-frequency signals are used for estimating the phase output of an echo, and the result is shown in fig. 5.
As can be seen from fig. 5, the phase feature of the target can be used as an effective feature for judging the property of the target material, and particularly for the classification of artificial metal targets and non-targets (fish swarms, etc.), the phase feature can be used as an effective echo feature.
It should be understood that equivalent substitutions and changes to the technical solution and the inventive concept of the present invention should be made by those skilled in the art to the protection scope of the appended claims.
Claims (2)
1. An echo phase feature extraction method based on a dual-frequency emission signal is characterized in that: the method comprises the following steps:
setting a transmitting signal:
and has the following components: omega2=μω1,
Then the reflected echo is
Where, phi is the phase jump caused by the target, phi is pi for a soft surface target, and phi is 0 for a hard surface target;
in order to estimate the value of phi, the target reflection echo is filtered through a band-pass filter to respectively obtain two wavelets:
for wavelet pR1Performing mu-fold frequency scale transformation, and then correlating with the wavelet pR2Conjugate multiplication is carried out to obtain:
the phase term 2 pi n mu in the formula is fuzzy phase caused by periodicity of complex exponential, and for discrete echo, the complex phase comparison sequence obtained by the above processingThe argument is (mu-1) phi +2 pi n mu, and for a given value of mu, the argument values for targets with different surface properties will be different.
2. The method for extracting echo phase features based on dual-frequency transmitting signals according to claim 1, characterized in that: when taking mu-3/2, the amplitude value corresponding to the echo of the hard surface target is 0, ± pi, and for the soft surface, the amplitude value is pi/2, -pi/2 or 3 pi/2, under the condition of no noise pollution, the amplitude values of the phase comparison sequence corresponding to the reflection echoes of the surface targets with different properties are distributed in different angle areas, namely, the phase characteristic distribution extracted for the different types of targets has obvious difference, and the hard and soft properties of the surface medium of the underwater scatterer are effectively represented.
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P.R.ATKINS ET AL.: "Transmit-Signal Design and Processing Strategies for Sonar Target Phase Measurement", IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING * |
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