Real-Time Identification Algorithm of Daylight Space Debris Laser Ranging Data Based on Observation Data Distribution Model

TL;DR

A new algorithm identifies space debris laser signals in daylight by analyzing statistical patterns, enabling real-time tracking in high-noise conditions.

Contribution

Proposes a statistical distribution-based method for real-time identification of weak laser echo signals in daylight.

Findings

The algorithm detects signals as low as 0.09 photons per pulse in high-noise conditions.

It achieves real-time identification within 1 second using a statistical distribution model.

The method outperforms traditional intensity threshold techniques.

Abstract

What are the main findings?
A statistical distribution-based algorithm is proposed to distinguish weak echo signals from intense daylight background noise, achieving real-time identification of space debris laser ranging data within 1 s.The method successfully detects echo signals with intensities as low as 0.09 photons per pulse under high-noise conditions (background noise rate: 2 × 107 photons/s), surpassing the traditional intensity threshold constraints.

A statistical distribution-based algorithm is proposed to distinguish weak echo signals from intense daylight background noise, achieving real-time identification of space debris laser ranging data within 1 s.

The method successfully detects echo signals with intensities as low as 0.09 photons per pulse under high-noise conditions (background noise rate: 2 × 107 photons/s), surpassing the traditional intensity threshold constraints.

What is the implication of the main finding?
Enables continuous daylight tracking and precise orbit determination of space debris in low signal-to-noise ratio (SNR) environments, which is critical for spacecraft safety.Leverages statistical distribution disparities instead of signal intensity, offering a universal framework for weak signal extraction in photon-starved regimes.

Enables continuous daylight tracking and precise orbit determination of space debris in low signal-to-noise ratio (SNR) environments, which is critical for spacecraft safety.

Leverages statistical distribution disparities instead of signal intensity, offering a universal framework for weak signal extraction in photon-starved regimes.

In an effort to accomplish the real-time acquisition of the laser ranging results of space debris during the daylight and enhance the observation success rate, this paper establishes a joint distribution model of noise and echo signals grounded on the intensity distribution law of the daylight background noise. Through an in-depth analysis of the measurement characteristics of single-photon detectors, a real-time recognition algorithm based on the disparity in statistical distribution is put forward. This algorithm partitions the observation data into intervals of equal length. It then employs the goodness-of-fit test of the geometric distribution to ascertain the data distribution law. Subsequently, it locates the interval in which the echo signal resides by analyzing the contribution degree of the chi-square statistic. The experimental outcomes indicate that under the circumstances of a laser frequency of 400 Hz and a background noise photon rate of 2 × 107 photons per second, the algorithm is capable of achieving real-time recognition of the echo interval for an intensity of 0.09 echo photons per single pulse within 1 s. This breakthrough resolves the critical challenge of daylight echo discrimination in high-noise environments. This method overcomes the constraints of the traditional signal intensity threshold and offers a novel technical approach for the tracking and precise orbit determination of space debris in a low signal-to-noise ratio environment.

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