Apparatus, method, and computer program for a resolution-enhanced pseudo-noise code technique

1. A space based low power high resolution 3D imaging docking lidar system using resolution-enhanced pseudo-noise coding apparatus, comprising:

an array of laser diodes including non-linear adaptive processor means for generating a plurality of unique patterns to be associated with a return to zero (RZ) signal, each laser diode configured to transmit said return to zero (RZ) signal to different locations simultaneously on a reflective moveable or non-movable object which reflects pulses;

a photo detector receiver for receiving each reflected RZ pulse from different locations on said object configured to receive each of the transmitted return to zero signals, identifying said reflective object,

wherein each of the return to zero signals comprises a unique, pattern to distinguish between itself and the other simultaneously transmitted return to zero signals.

2. The apparatus of claim 1 , further comprising:

a pattern generator configured to generate a plurality of unique patterns and drive the array of layer diodes, such that each of the laser diodes simultaneously transmits the return to zero signal to different locations on the object.

3. The apparatus of claim 1 , further comprising:

a scanner configured to direct each of the return to zero signals and transmit each of the return to zero signals to different locations on the object.

4. The apparatus of claim 1 , further comprising:

an optical filter configured to reduce optical domain noise in each received return to zero signal.

5. The apparatus of claim 1 , further comprising:

an array of detectors configured to detect each received return to zero signal.

6. The apparatus of claim 1 , further comprising:

an amplifier configured to amplify each detected return to zero signal.

7. The apparatus of claim 6 , further comprising:

an electronic filter configured to reduce electronic domain noise in each amplified return to zero signal.

8. The apparatus of claim 1 , further comprising:

a pattern generator configured to generate reference patterns to identify each of the return to zero signals based on the unique pattern included in each of the return to zero signals.

9. A method for using a space based low power high resolution 3D imaging docking lidar system using resolution-enhanced pseudo-noise coding for recognizing an object comprising:

transmitting, by each of a plurality of non-linear adaptive processor controlled laser diodes, a return to zero signal to different locations simultaneously on an object; and

receiving, by a photo detector receiver, each of the transmitted return to zero signals, identifying said reflective object,

wherein each of the return to zero signals comprises a unique pattern to distinguish between itself and the other transmitted return to zero signals.

10. The method of claim 9 , further comprising:

generating, by a pattern generator, a plurality of unique patterns; and

driving, by the pattern generator, each of the laser diodes such that each of the laser diodes simultaneously transmits the return to zero signal to different locations on the object.

11. The method of claim 9 , further comprising:

scanning, by a scanner, each of the return to zero signals; and

transmitting, by each of the plurality of laser diodes, each of the return to zero signals to different locations on the object.

12. The method of claim 9 , further comprising:

reducing, by an optical filter, optical domain noise in each received return to zero signal.

13. The method of claim 9 , further comprising:

detecting, by an array of detectors, each received return to zero signal.

14. The method of claim 9 , further comprising:

amplifying, by an amplifier, each detected return to zero signal.

15. The method of claim 14 , further comprising:

reducing, by an electronic filter, electronic domain noise in each amplified return to zero signal.

16. The method of claim 9 , further comprising:

generating, by a pattern generator, a plurality of reference patterns to identify each of the return to zero signals based on the unique pattern included in each of the return to zero signals.