LISA卫星上干涉仪数据获取： undersampling法实现窄带信号数字化

53 浏览量更新于2024-09-04 收藏 451KB PDF 举报

信号数字化通过下采样：LISA卫星上使用的干涉仪数据获取方法本文介绍了一种针对LISA（激光干涉仪空间天线，欧洲航天局/美国国家航空航天局合作的太空任务）卫星上将要使用的紧凑型激光干涉仪的数据获取与处理方法，特别关注于通过下采样技术对窄带信号进行数字化。LISA卫星的主要任务是作为自由漂浮质量位置和倾斜测量的光学读出演示器。该干涉仪的测量信号和参考信号与输入频率差(Δωt - φ(t))和输入频率(Δωt)成正比。其中，Δf = Δω / (2π)是干涉仪的混频频率，而φ(t)由随时间变化的长度差Δl(t)决定，表达为φ(t) = 4πλΔl(t)，其中λ是光波长。为了获取测量信号的相位φ(t)，通常采用正交测量法，通过测量两个信号S1 = 1/2 AB * cos(Δωt - φ(t)) 和 S2 = 1/2 AB * sin(Δωt - φ(t))，来得到干涉信号的完整信息。这种情况下，下采样是一种有效的策略，它允许在不牺牲信号质量的前提下减少硬件需求，包括数据采集系统和后续的信号处理。下采样是指在不改变信号本质的情况下，将原始信号以低于其最高频率的速率进行采样，从而降低数据传输速率和存储需求。在LISA这样的空间任务中，轻量化硬件对于减轻卫星负担、降低能耗以及提高系统的整体可靠性至关重要。通过实施下采样技术，本文提出了一种优化方案，旨在减小干涉仪的数据处理复杂性，同时保持测量精度。这不仅有助于简化硬件设计，还能提升系统的稳定性和长期运行能力，对于实现LISA的科学目标具有重要意义。关键词：数据获取、下采样、干涉仪在实际应用中，这种方法将涉及到信号恢复算法，确保在低采样率下能够准确地重构原始窄带信号。此外，可能还需要考虑噪声抑制和抗干扰措施，以确保在空间环境中获取到的信号质量不受影响。总体而言，这篇首发论文为LISA卫星上干涉仪数据处理技术提供了一个创新且实用的解决方案。

Signal digitalizing by undersampling, an approach for the

data acquisition of the interferometer to be used aboard the

LISA satellite

Wei Zhou, Claus Braxmaier

Hochschule f

ur Technik, Wirtschaft & Gestaltung,

Brauneggerstr. 55, 78462 Konstanz, Germany

Abstract:

We present a method for digitalizing narrowband signal by undersampling to

reduce the hardware for the data acquisition and processing of an interferometer.

Keywords: Data acquisition, undersampling, interferometer

1. Introduction

A compact laser interferometer for translation and tilt metrology has been presented in [1]. It

is going to serve as a demonstrator for an optical readout of the free-ﬂoating proof mass position

and tilt aboard the LISA (Laser Interferometer Space Antenna, a ESA/NASA collaborative space

mission) satellites.

The measurement signal i

and the reference signal i

are proportional to cos(∆ωt − φ(t)) and

cos(∆ωt) respectively. ∆f =

∆ω

2π

is the heterodyne frequency of the interferometer. φ(t) is given

by φ(t) =

4π

∆l(t). In order to obtain the phase of the measurement signal φ(t), in-quadrature

measurement has been used to get the two signals S

AB ·cos(φ(t)) and S

AB ·sin(φ(t)) at

ﬁrst. Then φ(t) can be calculated by φ(t) = tan

−1

(

). Fig. 1 shows the schematic of this technique.

Here, the measurement has bee n carried out by hardware. The computer merely computes the value

of tan

−1

(

). Of course the digitalizing of both signals i

and i

can be done directly at the output

of the interferometer, i.g. directly behind the diodes, so that the in-quadrature measurement can

be carried out by software on the computer. Even though quicker data acquisition units can be

used, the speed of computer gives the limit of real-time processing, because the quicker the data

acquisition is, the more data have to be processed in computer. Usually it is desirable to have a

higher heterodyne frequency to minimize the inﬂuence of noise. Consequently, a very hight speed

of the com puter would be necessary.

In this paper, data acquisition by deliberate undersampling is discussed. For phase signal φ(t),

which doesn’t change very fast, i.g. it has only a very narrow bandwidth, we will see that a high

sampling rate is not necessary, especially for static measurement, where φ(t) is a constant. In that

http://www.paper.edu.cn

下载后可阅读完整内容，剩余4页未读，立即下载

weixin_38747592

粉丝: 7
资源: 937

LISA卫星上干涉仪数据获取： undersampling法实现窄带信号数字化

模电资料section1--9

Why Oversample when Undersampling can do the Job.pdf

彭敏龙__Trainable Undersampling for Class-Imbalance Learning1

Algorithm-undersampling.zip

Oversampling, Undersampling and combinaion.py

a systematic study of the class imbalance problem.pdf

Data Converters

Double-hyperbolic undersampling & probabilistic benchmarks：双双曲欠采样滤波器去噪变量和相关向量机估计概率基准-matlab开发

create_balanced_train_test.zip_The Divide

Data_Converters

最新资源