CN104154934B

CN104154934B - Optimization defining method for the discrete point interval of hangover star image numerical simulation

Info

Publication number: CN104154934B
Application number: CN201410422979.1A
Authority: CN
Inventors: 王海涌; 宋振飞
Original assignee: Beihang University
Current assignee: Beihang University
Priority date: 2014-08-26
Filing date: 2014-08-26
Publication date: 2016-07-13
Anticipated expiration: 2034-08-26
Also published as: CN104154934A

Abstract

The present invention provides the optimization defining method at a kind of discrete point interval for hangover star image numerical simulation; realize step as follows: set discrete point interval and be not more than the mean square deviation of the dimensional Gaussian distribution function as point spread function; in hangover star image centrode segmental arc; choose limited discrete location sampled point; centered by these discrete points; set up dimensional Gaussian gray scale point spread function, all Gaussian diffusions are done superposition, obtain the curved surface profile smoothed.

Description

Optimization defining method for the discrete point interval of hangover star image numerical simulation

(1) technical field

The present invention relates to the optimization defining method at a kind of discrete point interval for hangover star image numerical simulation, belong to art of image analysis, be an optimisation technique realizing dynamic star image simulation.

(2) background technology

Star sensor is one of main attitude measuring of aircraft, and the maximum bottleneck restraining factors of its engineer applied are the motor-driven dynamic imaging hangovers caused of carrier.Star simulator is the experiment test device of star sensor, the verification test of the disposal ability of star sensor dynamic image, it is necessary to star simulator generates the dynamic star chart with hangover feature.Star image is dynamically trailed and has been badly influenced the function of star sensor, it is not possible to the dynamically adapting ability of the static star chart sequential test strapdown star sensor algorithm of recycling.

When star sensor relative inertness system's absolute rest, static star image is sub-circular, and energy approximation is dimensional Gaussian distribution, as shown in Figure 1.If strapdown carrier relative inertness system exists attitude maneuver, then produce corresponding tri-axis angular rate at star sensor body, cause that dynamic imaging trails.The energy of any pixel in desirable hangover star image coverage, is the Gaussian diffusion line integral along hangover track of amplitude attenuation, but it is long to do the line integral time in program, it is difficult to ensure real-time.

In engineer applied, dynamic star image generally adopts quick numerical integration method, according to star sensor three-axis attitude, tri-axis angular rate and optical system model, the hangover track of imaging surface sets limited discrete location points, centered by these discrete location points, set up dimensional Gaussian gray scale point spread function, all Gaussian diffusions are done superposition, the star image of dynamically trailing of arbitrary star in star sensor visual field can be simulated, as in figure 2 it is shown, the relative star sensor body of figure culminant star k has angular motion.On hangover track, the size at discrete location points interval directly affects the similarity of simulation hangover star image, and discrete location points interval is long, and stack result will produce Ripple Noise, as shown in Figure 3.Therefore, for dynamically hangover star image numerical simulation, the optimization defining method at this discrete point interval is adopted, it is possible to reach to take into account the analog simulation effect of real-time and similarity.

(3) summary of the invention

It is an object of the invention to provide the optimization defining method at a kind of discrete point interval for hangover star image numerical simulation.

It is an object of the invention to be achieved through the following technical solutions:

If certain hangover star image centrode is a segmental arc, this segmental arc is chosen limited discrete location sampled point, as the center of dimensional Gaussian gray scale point spread function, these Gaussian diffusions is done superposition.Finding by emulating, some interval is more little, and the result ripple amplitude after superposition is more little, and closer to the ideal hangover star image gabarit of integrated form, along with an interval increases, the ripple amplitude of stack result also can increase.When sampled point interval is not more than the meansquaredeviationσ of dimensional Gaussian distribution, after the Gauss distribution superposition of each discrete location points, obtain the contour surface smoothed.In being distributed due to dimensional Gaussian, two independent variable probability distribution are separate, the result being analyzed just for one-dimensional Gauss distribution is without loss of generality, Fig. 4 is the gabarit analogous diagram that under different discrete point spacing case, discrete Gaussian function curve combining obtains, discrete point is spaced apart 2 σ and 4 σ situations, contour curve after superposition has ripple, and 0.5 σ and 1 σ situation does not then have ripple.

(4) accompanying drawing explanation

Fig. 1 is the gray scale dimensional Gaussian distributed simulation figure of static star image；

Fig. 2 is dynamically trail imaging mechanism and method for numerical simulation schematic diagram；

Fig. 3 is that discrete point interval is more than dimensional Gaussian point spread function stack result analogous diagram under 1 σ situation；

Fig. 4 is the gabarit figure that in different interval situation, discrete Gaussian function curve combining obtains；

(5) detailed description of the invention

Illustrate below in conjunction with accompanying drawing 4 and the present invention be described in further detail and illustrate:

If the line segment that certain hangover track is in x-axis from-10 to 10, respectively with 4 σ, 2 σ, 1 σ, 0.4 σ for interval, this hangover track is chosen limited discrete location sampled point, as the center of Gauss gray scale point spread function, these Gaussian diffusions is done superposition.In being distributed due to dimensional Gaussian, two independent variable probability distribution are separate, and the result being analyzed just for one-dimensional Gauss distribution is without loss of generality.Being found by the emulation of one-dimensional Gauss distribution, some interval is more little, and the curved grain wave amplitude after superposition is more little, and calculates the ideal hangover star image gabarit obtained closer to mathematic integral, and along with an interval increases, the ripple amplitude of stack result also can increase.When sampled point interval is equal to 1 σ, the contour curve after the Gaussian distribution curve superposition of discrete location points is then very smooth, and ripple amplitude is less than 10^-7, as shown in Figure 4.

Investigate the superposition contour approximation tailed curve being spaced apart 1 σ, compare calculating with desirable tailed curve, coefficient R=0.9883 of two curves, Euclidean distance (root-mean-square error) RMS=0.0683 of two curves.Therefore, replace desirable tailed curve with hangover profile approximate formed by the static Gaussian function its superimposition of interval 1 σ, there is enough similarities.

Need exist for 2 points are described: 1. owing to imaging array is plane, rather than radius of curvature is the cambered surface of focal length, then in light integration time, hangover speed changes, requiring that the discrete point interval in fastest one end of trailing ensures and be not more than 1 σ, under sampling time equal condition, other discrete point interval is then less than 1 σ；2. calculate trailing length, mark off integer sampled point interval, and to ensure at the discrete point interval of fastest one end of trailing less than 1 σ, if producing sampled point to be spaced apart the division situation of decimal, the then Centre position deviation of star image of trailing after causing superposition.

Too much interval quantity can ensure that ripple-free after superposition, but can increase the calculating time of numerical simulation, although the very few amount of calculation that can reduce of the quantity at interval, but if there is the gap length situation more than 1 σ, then can produce Ripple Noise.Therefore, the method for optimization be the longest interval close to 1 σ, whole hangover centrode segmental arc can guarantee that again and marks off integer interval simultaneously.

Claims

1. for the optimization defining method at the discrete point interval of hangover star image numerical simulation, it is characterized in that, described method step is as follows:

(1) in hangover star image centrode segmental arc, choose limited discrete location sampled point, centered by these discrete location sampled points, set up dimensional Gaussian gray scale point spread function；

(2) set discrete location sampled point interval and be not more than mean square deviation 1 σ of dimensional Gaussian gray scale point spread function, all dimensional Gaussian gray scale point spread functions are done superposition, obtains the hangover star image curved surface profile smoothed；

(3) in light integration time dynamic process, speed of trailing in imaging array plane changes, trailing, fastest one end discrete location sampled point spacing value is set to 1 σ, when waiting when sampling step length other discrete location sampled point interval then less than 1 σ.