Method and apparatus for improved visual display of a target viewed by an imaging sensor device

• US 5,276,632 A
• Filed: 08/10/1990
• Issued: 01/04/1994
• Est. Priority Date: 08/10/1990
• Status: Expired due to Fees

• Current Assignee: Kaman Aerospace Corporation (Kaman Corporation)
• Original Assignee: Kaman Aerospace Corporation (Kaman Corporation)
• Inventors: Pflibsen, Kent, Calmes, Lonnie K., Richardson, Henry R., Stefanick, Tom A., Kuo, Stanley D., Corwin, Thomas L., Keeler, R. Norris
• Primary Examiner(s): CANGIALOSI, SALVATORE A
• Application Number:
  US07/565,480
• Time in Patent Office: 1,243 Days
• Field of Search: 364/570, 364/578, 358/95, 356/5
• US Class Current: 703/2
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G01S 7/4802 using analysis of echo signal for target characterisation; Target signature; Target cross-section
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes

Abstract

A novel data processing technique is provided for employing a physical model as an element in a process for automatic target detection of a target viewed by an imaging lidar system. The present invention obtains estimates for the mean and variance of the probability distributions for random video levels which are output from a camera. These estimates are obtained under various assumptions about the state of the target.

Claims

1. A method of visually displaying a target viewed by an imaging sensor means, the imaging sensor means including pulsed light source means and gated camera means and wherein the imaging sensor means is positioned on an airborne platform and images targets under water and wherein said gated camera means includes a focal plane and an entrance aperture, including the steps of:

a) calculating the hypothetical distributions of the number of photons impinging on the gated camera means using a hypothetical physical and optical model;

b) obtaining actual target data from targets imaged underwater by the imaging sensor means;

c) processing said actual target data;

d) delivering said actual target data to an automatic target detection system;

e) employing said calculated hypothetical distributions in said automatic target detection system by a comparison of said calculated hypothetical distributions with said processed actual target data to thereby improve in the detection of a target viewed by the imaging sensor means; and

f) visually displaying a target viewed by the imaging sensor means based on the improvement in target detection obtained from step (e).

2. The method of claim 1 including multiple processing units for parallel processing and including the step of:

calculating said hypothetical distributions in at least some of said multiple processing units.

3. The method of claim 1 wherein the hypothetical physical and optical model for calculating the hypothetical distribution of the number of photons impinging on the gated camera means of the imaging sensor means is determined from the steps of:

(1) calculating the mean and variance of the pulsed light source irradiance function F₁ at the depth of interest for the hypothesis under consideration;

(2) calculating the mean and variance of the resulting radiance function F₂ from the top surface of the depth stratum due to backscattering from the water volume and due to reflection or obscuration from the target if it is assumed present under the given hypothesis;

(3) calculating the mean and variance of the intensity function F₃ which is obtained from integrating the radiance function over the projected area of a pixel at the top surface of the depth stratum;

(4) calculating the means and variance of the power P₄ which is imaged on the focal plane of the camera means by integrating the intensity function F₃ over the solid angle subtended by the entrance aperture of the camera means and by accounting for attenuation and other transmission losses;

(5) calculating the mean and variance of the power P₅ reflected back into the camera means from the sun and sky;

(6) calculating the means and variance of the number of photons corresponding to the total energy received from and imaged on a pixel on the focal plane over the time duration of the camera means exposure gate width wherein said total energy corresponds to the sum of reflected laser energy and reflected sunlight and skylight energy; and

(7) calculating the mean and variance of the digitized pixel video levels on the focal plane to determine μ

_n O, σ

_n O and μ

_n,m^A and σ

_n,m^A.

4. The method of claim 3 wherein the variance is equal to the mean in step (1) and wherein the pulsed light source irradiance function F₁ of step (1) at a depth z is determined by the equation:

##EQU25## where τ

=pulse width in seconds;

A_beam (h,z)=area of the beam at depth z when the imaging sensor is at altitude h;

E_o =output energy of the pulsed light source;

T_out =transmission of the transmitter optics; and

Ψ

=averaging factor which converts the measured pulse energy to an average energy over the field of the gated camera means.

5. The method of claim 3 wherein the variance is equal to the mean in step (2) and wherein radiance function F₂ of step (2) a depth z_k corresponding to the top of the Kth depth gate and wherein the radiance function F₂ is expressed as power per unit area per unit solid angle in the direction and is determined by the following equation (1) when the target is present and the top surface of the target is at depth d, equation (2) when the target is above the depth stratum of interest and the returning energy is obscured and equation (3) when the target is not present and the returning energy is from volume backscattering alone:

##EQU26## where A_beam (h,z)=area of the beam at depth z when the imaging sensor is at altitude h.

6. The method of claim 3 wherein the variance is equal to the mean in step (3) and wherein the mean intensity function F₃ of step (3) at depth z is determined by equation (1) when the intensity of radiation from a region which is the projection of the (i,j)th pixel on the focal plane of the camera means, and equation (2) where the radiance does not vary significantly over the projected area of a pixel:

##EQU27## where f=focal length of the camera means;

n=reflective index of water;

A_pixel =area of a pixel on the focal plane of the camera; and

X_ij and Y_ij =points within the projection of the _ij th pixel.

7. The method of claim 3 wherein the variance is equal to the mean in step (4) and the man power P₄ of step (4) imaged on a pixel on the focal plane is determined by the equation:

space="preserve" listing-type="equation">F.sub.4 (i,j,k)=Ω

T.sub.in T exp(-kz.sub.k)F.sub.3 (i,j,k,π

)(1)

where

T_in =transmission of the optics of the camera means;

T=transmission of the air/water interface;

exp(-kz_k)=attenuation of the beam energy by the water; and

Ω

=solid angle of the entrance aperture of the camera means as seen from the point (X_ij, Y_ij, z_k).

8. The method of claim 7 wherein:

##EQU28## where D=diameter of the entrance aperture of the camera means.

9. The method of claim 3 wherein the variance is equal to the mean in step (5) and wherein the mean power P₅ of step (5) is determined by the equation:

##EQU29## where λ

=wavelength of the pulsed light source;

h=Planck'"'"'s constant;

c=speed of light in a vacuum;

I_sum =solar irradiance at the water surface;

T_in =incoming transmittance;

Γ

_water =diffuse reflection of surface;

A_pixel =area of a pixel on the focal plane of the camera means;

f#=f number of the camera means;

τ

_gate =gate width in dimensions of time; and

FWHM is the bandwidth of a filter associated with the camera means.

10. The method of claim 3 wherein the variance is equal to the mean in step (6) and wherein the mean number of photons corresponding to the total energy incident on a pixel on a focal plane is determined by equation (1) when the target is assumed present and the top surface of the target lies within the volume corresponding to the pixel index n, equation (2) when the target is assumed present, and the top surface of the target lies below the volume corresponding to the pixel index n, and equation (3) when the target is assumed not present and the mean number of the photons corresponding to index n under the mth hypothesis is denoted N_n :

##EQU30## where T_n,m =mean number of photons corresponding to index n under the mth hypothesis;

λ

=wavelength of the pulsed light source;

h=Planck'"'"'s constant;

c=speed of light in a vacuum;

T_in =incoming transmittance;

A_pixel =area of a pixel on the focal plane of the camera means;

f#=f number of the camera means;

T_out =outgoing transmittance (pulsed light source to water);

E_o =energy per pulse;

A_beam (h,z)=area of the beam at depth z when the imaging sensor is at altitude h; and

Ψ

=averaging factor which converts the measured pulse energy to an average energy over the field of view of the gated camera means.

13. The apparatus of claim 9 including multiple processing units for parallel processing and including:

means for calculating said hypothetical distributions in at least some of said multiple processing units.

11. In an automatic target detection system for use in an imaging lidar system having pulsed light source transmitter means and gated camera receiver means, the improvement comprising:

parallel processing computational units for processing hypothetical distributions of photons impinging on the gated camera means using a hypothetical physical and optical model.

12. An apparatus for visually displaying a target viewed by an imaging sensor means, the imaging sensor means including pulsed light source means and gated camera means and wherein the imaging sensor means is positioned on an airborne platform and images targets under water including:

a) means for calculating the hypothetical distributions of the number of photons impinging on the gated camera means using a hypothetical physical and optical model;

b) means for obtaining actual target data from targets imaged underwater by the imaging sensor means;

c) means for processing said actual target data;

d) means for delivering said actual target data to an automatic target detection system;

e) comparator means for employing said calculated hypothetical distributions in said automatic target detection system by a comparison of said calculated hypothetical distributions with said processed actual target data to thereby improve in the detection of a target viewed by the imaging sensor means; and

f) visual display means for visually displaying a target viewed by the imaging sensor means based on the improvement in target detection obtained from said comparator means.