阅读说明：本技术 一种天基红外空中目标探测波段选取方法 (Space-based infrared aerial target detection waveband selection method ) 是由 饶鹏 朱含露 陈略 于 2021-07-15 设计创作，主要内容包括：本发明公开了一种天基红外空中目标探测波段选取方法,首先系统性地建立了空中目标整体在红外波段的辐射特性模型,再建立几种常见背景的辐射特性模型；以目标和背景的辐射特性为基础,结合信噪比(SNR)和信杂比(SCR)提出信号-噪声-杂波联合比(SNCR),以SNCR作为评价标准对目标整体辐射特性强度进行评估；分别计算空中目标在不同波段区间内的SNCR值,确定SNCR的峰值区间,并以此区间作为天基空中目标的探测波段。本方法可为提升天基红外探测系统获取到的目标信号强度提供依据,提高目标与背景杂波、系统噪声的对比度,显著提升探测系统对空中目标的发现能力。(The invention discloses a space-based infrared aerial target detection waveband selection method, which comprises the steps of firstly systematically establishing a radiation characteristic model of an aerial target whole in an infrared waveband, and then establishing several radiation characteristic models of common backgrounds; based on the radiation characteristics of the target and the background, a signal-to-noise-clutter combination ratio (SNCR) is provided by combining a signal-to-noise ratio (SNR) and a signal-to-clutter ratio (SCR), and the SNCR is used as an evaluation standard to evaluate the overall radiation characteristic intensity of the target; and respectively calculating the SNCR values of the aerial target in different wave band intervals, determining the peak value interval of the SNCR, and taking the interval as the detection wave band of the aerial target on the space basis. The method can provide a basis for improving the signal intensity of the target acquired by the space-based infrared detection system, improve the contrast between the target and background clutter and system noise, and obviously improve the discovery capability of the detection system on the aerial target.)

1. A space-based infrared aerial target detection waveband selection method is characterized by comprising the following steps: the method comprises the following steps:

the method comprises the following steps: collecting various parameters of common aerial targets and different types of backgrounds, constructing target and background radiation characteristic models, and respectively obtaining the relation phi between the radiation flux of the target and the background and the wavelength_tar(lambda) and phi_bk(λ), where φ is the radiant flux and λ is the wavelength;

step two: defining clutter according to the statistical variance method of Silk, and further obtaining the signal-to-noise ratio SCR (lambda) in the space-based target detection process₁,Δλ)：

Step three: defining the signal-to-noise ratio: conversion of the radiant flux of the signal into a number N of signal electrons_S(λ₁Δ λ), as follows:

N_S(λ₁,Δλ)＝φ_q·η·t_int(e/pixel) (4)；

signal to noise ratio SNR (λ)₁Δ λ), the expression is as follows:

step four: combining the formulas (3) and (5) to obtain the SNCR joint parameter formula:

step five: combining the formula (6) to obtain the initial wave band lambda of the space-based aerial target detection_intAnd a wavelength interval lambda_dif：

2. The space-based infrared aerial target detection waveband selection method according to claim 1, characterized in that: the relation phi between the radiant flux of the target and the wavelength in the step one_tarDetermination of (λ):

comprehensively analyzing the radiation characteristics of the aerial target, constructing a radiation characteristic model of the target from the geometric dimension, the motion characteristics, the skin temperature, the emissivity of the skin and the tail flame, and the temperature change of the tail nozzle and the tail flame of the target, and obtaining the spectral radiation flux phi of the target_tar(λ) dependence on wavelength λ:

wherein, I_tar(lambda) is the target radiation intensity, R isThe satellite orbit height, H is the target ground height, n is the pixel number on the target refocus plane, tau (lambda) is the atmospheric transmittance, tau₀(λ) is the optical system efficiency, K (λ) is the energy concentration, A_rIs the entrance pupil area.

3. The method for selecting the sky-based infrared aerial target detection waveband according to claim 2, characterized in that: the relation phi between the radiation flux of the background and the wavelength in the step one_tarDetermination of (λ):

the main radiation sources causing background radiation are the sun, the atmosphere, clouds and ground objects, and the solar radiation influences the radiation characteristics of the target by reflecting or scattering in a direct or indirect way; the earth surface emits radiation and scatters earth surface radiation for many times; atmospheric self-thermal radiation and environmental radiation scattering, and the superposition of the radiation sources is total background radiation; analyzing the several main background radiation sources to obtain a background radiance radiation characteristic model L_bk(λ), further finding the background radiant flux:

φ_bk(λ)＝I_bk(λ)Ωτ(λ)τ₀(λ)K(λ)A_r (2)

where Ω is the instantaneous field solid angle.

4. The method for selecting the sky-based infrared aerial target detection waveband according to claim 3, wherein the method comprises the following steps: in the step two, in the formula,as a starting wavelength λ₁The mean value of the target radiation flux of the band width Delta lambda is the target spectral radiation flux phi_tar(lambda) the integral over this band,as a starting wavelength λ₁Background radiation flux mean value in a local range around the target of the band width Δ λ; sigma_φc(λ₁Δ λ) is the background radiation in the local area around the objectStandard deviation of the emitted flux.

5. The space-based infrared aerial target detection band selection method according to claim 4, characterized in that: phi in the third step_qIs the flux of photon radiation, photon · s, on the photosurface^-1Eta is quantum efficiency, t_intIs the integration time; n is a radical of_S(λ₁Δ λ) is the number of electrons of the photocurrent signal over the band Δ λ, N_rdFor read noise over the band Δ λ, N_dDark current noise over the band Δ λ.

Technical Field

The invention belongs to the technical field of infrared remote sensing and infrared space, and particularly relates to a space-based infrared aerial target detection waveband selection method.

Background

When the target is detected under the remote condition, the detection distance is long, the signal of the target is weak, the background clutter is complex, the noise of the detector is obvious, and the detection effect is mainly influenced by three aspects: the first is the diversity of background changes, such as sea background, cloud background, city background, etc., of the target in the flight process, so that there are strongly varying background clutter; secondly, the influence of atmosphere, the target radiation can be selectively absorbed by some gases in the atmosphere or scattered by the atmospheric suspended particles in the process of penetrating the atmosphere, and the target radiation can be attenuated by the phenomena, so that the signal-to-noise ratio and the signal-to-noise ratio are reduced; in a third aspect, noise in the detector can also cause significant interference with the target signal. It is therefore necessary to acquire a large signal-to-noise ratio and signal-to-noise ratio so that the detector acquires a strong signal. Scholars at home and abroad mainly determine the spectral band of a target by only adopting a single parameter, and key parameters influencing the detection spectral band cannot be comprehensively and systematically considered.

Disclosure of Invention

In order to overcome the problems, the invention provides a space-based infrared aerial target detection waveband selection method.

The technical scheme adopted by the invention is as follows:

a space-based infrared aerial target detection waveband selection method comprises the following steps:

the method comprises the following steps: collecting various parameters of common aerial targets and different types of backgrounds, constructing target and background radiation characteristic models, and respectively obtaining the relation phi between the radiation flux of the target and the background and the wavelength_tar(lambda) and phi_bk(λ), where φ is the radiant flux and λ is the wavelength;

step two: defining clutter according to the statistical variance method of Silk, and further obtaining the signal-to-noise ratio SCR (lambda) in the target detection process₁，Δλ)：

Step three: defining the signal-to-noise ratio: conversion of the radiant flux of the signal into a number N of signal electrons_S(λ₁Δ λ), as follows:

N_S(λ₁，Δλ)＝φ_q·η·t_int(e/pixel) (4)；

signal to noise ratio SNR (λ)₁Δ λ), the expression is as follows:

step four: combining the formulas (3) and (5) to obtain the SNCR joint parameter formula:

wherein, the relationship phi between the radiant flux of the target and the wavelength in the step one_tarDetermination of (λ):

comprehensively analyzing the radiation characteristics of the aerial target, constructing a radiation characteristic model of the target from the geometric dimension, the motion characteristics, the skin temperature, the emissivity of the skin and the tail flame, and the temperature change of the tail nozzle and the tail flame of the target, and obtaining the spectral radiation flux phi of the target_tar(λ) dependence on wavelength λ:

wherein, I_tar(lambda) is the target radiation intensity, R is the satellite orbit height, H is the target ground height, n is the pixel number on the target refocus plane, tau (lambda) is the atmospheric transmission rate, tau₀(λ) is the optical system efficiency, K (λ) is the energy concentration, A_rIs the entrance pupil area.

Wherein, the relation phi between the radiation flux of the background and the wavelength in the step one_tarDetermination of (λ):

the main radiation sources causing background radiation are the sun, the atmosphere, clouds and ground objects, and the solar radiation influences the radiation characteristics of the target by reflecting or scattering in a direct or indirect way; the earth surface emits radiation and scatters earth surface radiation for many times; atmospheric self-thermal radiation and environmental radiation scattering, and the superposition of the radiation sources is total background radiation; for these severalAnalyzing the main background radiation source to obtain a background radiance radiation characteristic model L_bk(λ), further finding the background radiant flux:

φ_bk(λ)＝I_bk(λ)Ωτ(λ)τ₀(λ)K(λ)A_r (2)

where Ω is the instantaneous field solid angle.

Wherein, in the step two, in the Chinese formula,as a starting wavelength λ₁The mean value of the target radiation flux of the band width Delta lambda is the target spectral radiation flux phi_tar(lambda) the integral over this band,as a starting wavelength λ₁Background radiation flux mean value in a local range around the target of the band width Δ λ; sigma_φc(λ₁Δ λ) is the standard deviation of the background radiant flux in a local area around the target.

Wherein phi in the third step_qIs the flux of photon radiation, photon · s, on the photosurface^-1Eta is quantum efficiency, t_intIs the integration time; n is a radical of_S(λ₁Δ λ) is the number of electrons of the photocurrent signal over the band Δ λ, N_rdFor read noise over the band Δ λ, N_dDark current noise over the band Δ λ.

The invention has the following advantages:

according to the invention, the plume simulation model is established, the target radiation characteristic is comprehensively established, the detection spectrum is analyzed by combining the SNCR (selective non-catalytic reduction) joint indexes of the SNR (signal-to-noise ratio) and the SCR (signal-to-noise ratio), the reasonable specific spectrum aiming at the detection of the airplane target is finally determined, the target component in the signal output by the detection system is maximized as much as possible, and the detection probability of the aerial target is improved.

Drawings

FIG. 1 is a block flow diagram of the present invention;

FIG. 2 is a prototype of two different object models of the present invention, (a) type 1, (b) type 2;

Detailed Description

The present invention will be further described below, but the present invention is not limited to these.

A space-based infrared aerial target detection waveband selection method comprises the following steps:

the method comprises the following steps: collecting various parameters of common aerial targets and different types of backgrounds, constructing target and background radiation characteristic models, and respectively obtaining the relation phi between the radiation flux of the target and the background and the wavelength_tar(lambda) and phi_bk(λ), where φ is the radiant flux and λ is the wavelength;

radiation flux vs. wavelength of the target_tarDetermination of (λ):

comprehensively analyzing the radiation characteristics of the aerial target, constructing a radiation characteristic model of the target from the geometric dimension, the motion characteristics, the skin temperature, the emissivity of the skin and the tail flame, and the temperature change of the tail nozzle and the tail flame of the target, and obtaining the spectral radiation flux phi of the target_tar(λ) dependence on wavelength λ:

wherein, I_tar(lambda) is the target radiation intensity, R is the satellite orbit height, H is the target ground height, n is the pixel number on the target refocus plane, tau (lambda) is the atmospheric transmission rate, tau₀(λ) is the optical system efficiency, K (λ) is the energy concentration, A_rIs the area of the entrance pupil;

background radiant flux vs. wavelength phi_tarDetermination of (λ):

the main radiation sources causing background radiation are the sun, the atmosphere, clouds, ground objects and the like, and the solar radiation influences the radiation characteristics of the target by reflecting or scattering in a direct or indirect mode; the earth surface emits radiation and scatters earth surface radiation for many times; atmospheric self-thermal radiation, environmental radiation scattering and the like, and the superposition of the radiation sources is total background radiation; analyzing the several main background radiation sources to obtain background radiance radiationCharacteristic model L_bk(λ), further finding the background radiant flux:

φ_bk(λ)＝I_bk(λ)Ωτ(λ)τ₀(λ)K(λ)A_r (2)

where Ω is the instantaneous field solid angle;

step two: defining clutter according to the statistical variance method of Silk, and further obtaining the signal-to-noise ratio SCR (lambda) in the target detection process₁，Δλ)：

In the formula (I), the compound is shown in the specification,as a starting wavelength λ₁The mean value of the target radiation flux of the band width Delta lambda is the target spectral radiation flux phi_tar(lambda) the integral over this band,as a starting wavelength λ₁Background radiation flux mean value in a local range around the target of the band width Δ λ; sigma_φc(λ₁Δ λ) is the background radiant flux standard deviation in the local range around the target;

step three: defining the signal-to-noise ratio, converting the radiant flux of the signal into the number of signal electrons N_S(λ₁Δ λ), as follows:

N_S(λ₁，Δλ)＝φ_q·η·t_int(e/pixel) (4)

wherein phi is_qIs the flux of photon radiation, photon · s, on the photosurface^-1Eta is quantum efficiency, t_intIs the integration time; signal to noise ratio SNR (λ)₁Δ λ), the expression is as follows:

wherein N is_S(λ₁Δ λ) is the number of electrons of the photocurrent signal over the band Δ λ, N_rdFor read noise over the band Δ λ, N_dDark current noise at a band Δ λ;

step four: combining the formulas (3) and (5) to obtain the SNCR joint parameter formula:

examples

Simulation environment: matlab2018 b;

test input: in fig. 2, the basic parameters and the tail flame parameters of the two types of targets, the parameters of the track height, the read noise, the quantization bit number, the wave band range and the like of the simulation detection system, and different background parameters are shown.

It is noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.