Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)


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Finally Appendix A provides some supplementing algorithms for ionospheric intersection point IPP position vector computation, which is needed for the ionospheric media calibrations computation. Three key points were important when working out the concept for this new in-house media calibrations service: independency from external especially non-ESA sources in terms of data, models and software as far as possible. So the essentials of tropospheric calibrations provided by JPL JPL, are summarized in the following for a better understanding of the own new approach, Section 3.

The seasonal model parameters are delivered to the user in form of a time-normalized Fourier series representation, separately for the ZWD and ZHD:. The seasonal models, as well as the JPL media calibrations in general, are delivered to the users in the Control Statement Processor CSP format JPL, ; on top of these ZWD and ZHD background calibrations, time series of delta-corrections of tropospheric zenith delays, wet and dry, are derived from near-real-time weather and GPS data and delivered to the users in form of normalized-time polynomial representations:.

The Eq. The user has then to calculate the actual tropospheric zenith delay, separately for wet and dry, as sum of the value obtained from the seasonal model background plus the delta-correction computed with the actual polynomial. Such a CSP-file is generated once per day for the day before in rapid mode. In final mode the same process is repeated with 4 days latency and more GNSS observation data.

Each polynomial representation, Eq. Before entering into the polynomial fit, Eqs. The WEST data comprise, among others, temperature, pressure and humidity;.

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On the other hand, Flight Dynamics prefers, due to its systems setup, to get its tropospheric calibrations referred to the Saastamoinen Model, with the dry part computed from WEST data pressure measurements. Processing is done in rapid and in final mode. In rapid mode, this computer run is submitted via an automatic job scheduler crontab every day at UT and covers the time interval from UT of today observation day 48 h backwards to UT of the day before yesterday.

In final mode, the same process is repeated at UT, 4 days after the end of the observation day, with more observation data. The 48 h run of each day is processed independently of the other days. In order to avoid jumps at the interfaces between one polynomial representation and the next, the eight 6 h polynomials sequence is fitted to the complete 48 h delta-zenith delays series within one fitting process, as indicated in Eq.

In order to suppress jumps at the interfaces, constraints are introduced between successive polynomial representations in terms of offset, slope and slope rate, depending on the user's setting. Constraints are introduced between two successive polynomial representations in terms of conditional Eqs. The polynomial arguments are computed according to Eq.

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The interface epoch between the two successive polynomial representations is defined by the end time E P of the preceding polynomial P X , which is equal to the start time S Q of the subsequent polynomial Q Y , i. Putting these values for T into Eq. There is an agreement with Flight Dynamics that the polynomial representation for the tropospheric media calibrations should be of polynomial degree Four. This choice was a consequence of a trial and error process, during which it was observed that in some cases high degree polynomials were following the noise of the zenith delay estimates, which are uncorrelated and not smoothed, thus creating artificial slopes in the calibrations that were worsening the results.

Equation 5 displays the observation equations structure of two successive polynomial representations P X and Q Y with the interface constraints between them.

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These constraining equations are multiplied with weights W offs , W slpe , W slrt , which can be set by the user. An introduction of a Zero-weight leads to a non-constraining of the respective parameter, i. In the ideal case, the interface epochs of the eight polynomial representations coincide with measurement epochs of the tropospheric zenith delays. For the sake of simplicity and better readability, Eq. For simplicity, only three tropospheric zenith delay epochs are shown for each polynomial representation. So, in summary, one A-matrix is set up and solved in a least squares fit to obtain the estimated coefficients for all polynomials.

Equation 5 and Figure 2 represent the ideal case in terms of full tropospheric zenith delay data availability and tropospheric zenith delay epochs coinciding with the interface epochs of the eight polynomial representations.

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However, deviations in tropospheric zenith delay values availability and distribution from these ideal conditions can happen in daily routine operational processing. The constraining equations will, nevertheless, be established at the interface epoch;. This processing scheme is retained as long as at least one observable falls into the respective time interval.

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This approach of setting the polynomial degree generally to One or Zero in case of sparse data is to avoid oscillations that may propagate into the neighbouring polynomials;. Obviously the constraining scheme, Eqs. The neighbouring polynomials enclosing the affected 6 h time interval remain almost unaltered. Expressed in CSP-format, the four central 6 h polynomials blue in Fig. So the essentials of ionospheric calibrations provided by JPL JPL, shall be summarized in the following for a better understanding of the own new approach, Section 4. For delta-DOR observations, the quasar direction as function of time is required too.

As with the tropospheric calibrations, also for the ionospheric calibrations an approach has been worked out, which is based on own GNSS tracking data recorded and evaluated by the Navigation Support Office. This approach is simple, robust and easy to handle, relying as far as possible on in-house data and software and being as far as possible independent from external sources. Thus per day an ionospheric media calibration is computed covering the hours timespan from 0 h UT of today observation day back to 0 h UT of the day before yesterday.

As with the troposphere, also ionosphere processing is conducted in rapid and in final mode.

In rapid mode, this job is submitted via an automatic job scheduler crontab every day at UT. In order to avoid short, truncated passes at the beginning and at the end of this hours timespan, only those passes are considered which fall completely into the hours interval.

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All other passes are considered in the jobs of the day before or after. In final mode, the same processing is repeated at UT, 4 days after the end of the observation day. It should be noted that these DCBs cannot be estimated in an absolute sense so a certain reference datum has to be defined. This is done by specifying that the sum of the satellite DCBs is Zero. To avoid significant day-to-day variations in the DCB estimates, e. This smooths out the day-to-day variations and avoids jumps due to satellites missing on individual days, e.

The following weighting function was selected for the ionospheric media calibrations: 8. Tests, however, showed that Eq. The above principal approach, Eqs. An alternative to directly processing the sTEC values, is to map them with a mapping function, Eq. With Eq.

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By solving Eq. The computation of the IPP position vectors is described in Appendix A , whereby here the unit vector pointing into range direction is already known, Eq. Thus a probably higher weight is appointed to GNSS 2 as it in reality would deserve. So Eq. Before the cosine values obtained with Eq. Instead of the cosine values obtained from Eq. The weighted mean sTEC value computed with Eq. The right hand side of Eq. Unit vector pointing from ground station into the direction of weighted mean s TEC , Eq.

To account for the actual ionospheric activity level, corresponding to the actual ionospheric overall charge w. In addition, by applying this correction, also the situation of unfavourable geometrical conditions will be mitigated, e. A description of the figure details and all curves displayed and their meaning is also provided beneath Figure Theoretically, Eqs.

Of course the algorithm will in practice not be applied in this way, but this indicates that it is very robust and stable, and thus well suited for operational use. Davies, ; Komjathy, w. This frequency was selected to be consistent with the current processing system set up at Flight Dynamics.

Finally, a normalized-time polynomial of degree Five, Eq. One polynomial is fitted per pass. An implementation of media calibration extrapolations has so far not been considered and is not planned for the time being. Following are some more pictures from Goldstone, and ways to find out more.


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Photo: Bill Dunford DSS at Mars Station, the meter antenna used for tracking the most distant spacecraft and even for imaging asteroids with radar. You really have to stand there to appreciate its scale—the bus would easily fit inside the dish. Notice how the sunlight is focused on the reflector at the tip of the antenna, just like the invisible radio waves from the distant spacecraft it was talking with at the moment. Photo: Bill Dunford Welcome to the machine.

Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series) Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)
Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series) Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)
Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series) Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)
Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series) Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)
Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series) Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)
Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series) Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)
Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series) Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)
Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series) Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)
Low-Noise Systems in the Deep Space Network (JPL Deep-Space Communications and Navigation Series)

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