Telemetry Frames Research Articles

Different Long Short-Term Memory Approaches to Enhance Prediction-Based Satellite Telemetry Compression

Motivated by the success of deep learning in recent years, prediction-based methods are used to compress satellite telemetry data. In this paper, two-stage lossless compression methods for telemetry data are demonstrated. In the first stage, different approaches of long short-term memory (LSTM) based on one-to-one, many-to-one, and many-to-many network architectures are presented. The framework of implementing each approach, as a predictor, is discussed. In the second stage, a set of competing entropy coding methods are tested and evaluated. The presented approaches are capable of exploring correlation dependencies between consecutive samples in the individual and/or successive telemetry frames. The proposed approaches are introduced in two different versions: stacked- and nonstacked-based LSTM architectures trying to achieve higher prediction efficiency. The proposed approaches are tested on real telemetry data, in frames of different data word widths, in distinct FUNcube satellite sessions. The performance of each presented approach, as a predictor, is evaluated based on prediction gain, and reduction in entropy. However, the performance of the whole two-stage lossless compression method is assessed by compression ratio. Comparative analysis is preformed among the proposed approaches, and the improvements are verified against the state-of-the-art prediction-based approaches.

Automated support for spacecraft onboard equipment design on the basis of a heterogeneous model

This article presents methods and software tools for modeling and analysis of space system onboard equipment operation. The authors suggest the design of a heterogeneous model uniting knowledge bases and virtual devices simulating work of data reception and transmission equipment. Model design considers tasks appearing during preparation of satellite production at a company-manufacturer of the space industry. The model can be used at the stages of designing and testing of the onboard equipment. For design support, the model allows assessment of parameters of the reception-and-transmission path and of destabilizing factor influence on communication line quality. For ground test support, the model simulates functions of the onboard equipment during command-and-software control of a spacecraft, providing reception and transmission methods for a wide range of commands and methods of generation of telemetry frame values. The comparison of precedents obtained during simulation tests with the results of the finished equipment testing, allows determination of special features of the onboard system operation that can stay unnoticed if other methods of test preparation and analysis are applied.

A two-stage rice-based lossless compression method for telemetry data

The article presents results of a study of a proposed lossless compression method for telemetry data. A two-stage scheme of lossless compression, consisting of decorrelation and entropy coding, is presented. In experiments, a bitwise XOR operation is implemented as a decorrelator and rice coding method as entropy coder. A comparison is performed between two compression methods: one is based only on rice coding method, while the other is based on the proposed method. The results are based on estimates of the gain in variance and entropy of the output signal from the decorrelator. In experiments, parameters of telemetry information of automatic control systems are studied, such as temperature, pressure and positioning data. Streams of telemetry frames, with different frame structures: one and two level of commutation, in IRIG-106 standard format, are formed and tested. Based on experimental results, conclusions are done for lossless telemetry data compression.

Mars solar conjunction prediction modeling

During the Mars solar conjunction, telecommunication and tracking between the spacecraft and the Earth degrades significantly. The radio signal degradation depends on the angular separation between the Sun, Earth and probe (SEP), the signal frequency band and the solar activity. All radiometric tracking data types display increased noise and signatures for smaller SEP angles. Due to scintillation, telemetry frame errors increase significantly when solar elongation becomes small enough. This degradation in telemetry data return starts at solar elongation angles of around 5° at S-band, around 2° at X-band and about 1° at Ka-band. This paper presents a mathematical model for predicting Mars superior solar conjunction for any Mars orbiting spacecraft. The described model is simulated for the Mars Orbiter Mission which experienced Mars solar conjunction during May–July 2015. Such a model may be useful to flight projects and design engineers in the planning of Mars solar conjunction operational scenarios.

Lossless Compression of Telemetry Information using Adaptive Linear Prediction

Normal requirement for telemetry data compression algorithms is an ability to recover ini-tial data “as is” without loss of information. This feature is very important in various telemetry processing applications. Precise recovery of the telemetry data as it is acquired from the original source of information is necessary for the analysis of any kind of abnormal events, recovery of bad sites within the telemetry data stream and for other types of post- or real-time data pro-cessing [1,2]. The effectiveness of methods of lossless compression is largely determined by the properties of the data under compression [3]. Compression algorithms show better compression ratios if they can adapt to the characteristics of the input data, which are in most cases rapidly change. In this paper we present the results of studies conducted to develop an efficient method of reversible telemetry data compression based on adaptive linear prediction of telemetry data packed according to IRIG-106 format. IRIG-106 is an open standard, developed specifically for aerospace industry, but now used in wide range of telemetry registration applications [4]. Data is packed to frames of fixed length and predefined internal structure. Frame can carry different sources of information: digitized samples of analog signals, as well as pure digital data. For each source a channel of the recording system is provided. The source sample in each channel is in-troduced by telemetry word. All words in the frame have the same bit width. Telemetry frame contains additional service information in purpose of detecting bit errors, frame synchronization, etc. Lossless data compression algorithm can be divided into two stages; the first stage -

Flight test data cycle map optimisation

Flight testing of aircraft, in which new design concepts, problems, and deficiencies are examined, involves the collection of large quantities of data allocated onto blocks within a telemetry frame or data cycle map (DCM). Individual parameters are sampled at different rates and may vary in both their word length and the number of words used to represent them. Planning flight tests requires that the order in which data is placed on telemetry frames is predetermined, along with other limitations such as, the length of the frames and periodic placement of parameters. This process is usually performed manually with some computer assistance, but typically involves several week’s work. As flight tests become more complex, restrictions on bandwidth and personnel have become limiting factors. We present an algorithm for designing DCMs which involves a novel combination of some number theoretic results and a set covering model. Given a quantity of data to fit into a DCM, number theoretic analysis, including use of the Chinese remainder theorem, is used to establish the existence of DCMs of minimal length, which are then found using a set covering integer programming formulation. A comparison of efficiencies for this algorithm and DCM designs produced by AutoTelem™ will be discussed.