Engineering topics
Publications and source records attributed to Swanson, L..
This paper will present this roadmap, describe how it will support an increasing mission set while also providing significantly increased science data return, summarize the current state of key Ka-band and optical communications technologies, and identify critical path items in terms of technology developments, demonstrations, and mission users.
The exploration of the solar system by unmanned spacecraft is one of the triumph of the 20th century. The dramatic photographs of Mercury, Venus, Mars, Jupiter, Saturn, Uranus, and Neptune transmitted by spacecraft with romantic names like Mariner, Voyager, Viking, etc. over distances of hundreds of millions, even billions, of miles, have made these planets, which were previously known to us only as fuzzy telescopic images in textbooks, as real to us in the 1990's as, say, the Himalayas, the Sahara Desert, or Antarctica.
The purpose of a tail sequence for command link transmission units is to fail to decode, so that the command decoder will begin searching for the start of the next unit. A tail sequence used by several missions and recommended for this purpose by the Consultative Committee on Space Data Standards is analyzed. A single channel error can cause the sequence to decode. An alternative sequence requiring at least two channel errors before it can possibly decode is presented. (No sequence requiring more than two channel errors before it can possibly decode exists for this code.)
The Big Viterbi Decoder (BVD), currently under development for the DSN, includes three separate algorithms to acquire and maintain node and frame synchronization. The first measures the number of decoded bits between two consecutive renormalization operations (renorm rate), the second detects the presence of the frame marker in the decoded bit stream (bit correlation), while the third searches for an encoded version of the frame marker in the encoded input stream (symbol correlation). A detailed account of the operation is given, as well as performance comparison, of the three methods.
For a concatenated coding system, the effect of interleaving depth on interleaved frame-error rate is compiled by simulation. Comparisons are made for three different inner convolutional codes; all three systems have a (255,223) 8-bit Reed-Solomon code as an outer code. For all the inner convolutional codes tested, an interleaving depth smaller that 4 causes substantial loss.
Results are reported on the performance of the Deep Space Network's frame synchronizer for the (15,1/4) convolutional code after Viterbi decoding. The threshold is found that optimizes the probability of acquiring true sync within four frames using a strategy that requires next frame verification.
Channel and source coding theories are discussed. The following subject areas are covered: large constraint length convolutional codes (the Galileo code); decoder design (the big Viterbi decoder); Voyager's and Galileo's data compression scheme; current research in data compression for images; neural networks for soft decoding; neural networks for source decoding; finite-state codes; and fractals for data compression.
The performance (bit-error rate vs. signal-to-noise ratio) of two different interleaving systems, block interleaving and the newer helical interleaving are compared. Both systems are studied with and without error forecasting. Without error forecasting, the two systems have identical performance. When error forecasting is used with shallow interleaving, helical interleaving gains, but less than 0.05 dB, over block interleaving. For higher interleaving depth, the systems have almost indistinguishable performance.
The analysis used to generate the theoretical models showing the performance of the frame synchronizer is described for various frame lengths and marker lengths at various signal to noise ratios and bit error tolerances.
It is a fact that adjacent pixels in a Voyager image are very similar in grey level. This fact can be used in conjunction with the Maximum-Likelihood Convolutional Decoder (MCD) to decrease the error rate when decoding a picture from Voyager. Implementing this idea would require no changes in the Voyager spacecraft and could be used as a backup to the current system without too much expenditure, so the feasibility of it and the possible gains for Voyager were investigated. Simulations have shown that the gain could be as much as 2 dB at certain error rates, and experiments with real data inspired new ideas on ways to get the most information possible out of the received symbol stream.
A frame synchronization method based on an examination of the shortest bit length containing all error bursts is introduced. It is shown that the new method is more reliable and efficient than the commonly used one based on counting the number of errors for the convolutionally coded channel.
In relation to a problem in optical communication, the paper considers the general problem of maximizing the entropy of a stationary radom process that is subject to an average transition cost constraint. By using a recent result of Justesen and Hoholdt, an exact solution to the problem is presented and a class of finite state encoders that give a good approximation to the exact solution is suggested.
It is well known that for the Gaussian broadcast channel, timeshared coding is not as efficient as more sophisticated broadcast coding strategies. However, the relative advantage of broadcast coding over timeshared coding is shown to be small if the signal-to-noise ratios of both receivers are small. One surprising consequence of this is that for the wideband Gaussian broadcast channel, which is defined, broadcast coding offers no advantage over timeshared coding at all, and so timeshared coding is optimal.
Upper bounds on the decoder error probability for Reed-Solomon codes are derived. By definition, decoder error occurs when the decoder finds a codeword other than the transmitted codeword; this is in contrast to decoder failure, which occurs when the decoder fails to find any codeword at all. The results imply, for example, that for a t error correcting Reed-Solomon code of length q - 1 over GF(q), if more than t errors occur, the probability of decoder error is less than 1/t! In particular, for the Voyager Reed-Solomon code, the probability of decoder error given a word error is smaller than 3 x 10 to the minus 14th power. Thus, in a typical operating region with probability 100,000 of word error, the probability of undetected word error is about 10 to the minus 14th power.
Symbol stream combining has been proposed as a method for arraying signals at different antennas. If the received symbol streams are recorded on tape, it is desirable to limit the required storage without significantly affecting the performance. It is shown that 4-bit quantized symbols introduce an E sub b/N sub o penalty of only 0.05 dB.
Maximum Likelihood Convolutional Decoding, which is used by the Deep Space Network for short constraint-length convolutional codes, assumes that all strings of information bits are equally likely. In some cases, like image data, this is not the case. The use of information about an adjacent pixel in decoding convolutionally encoded Voyager images is examined. It is discovered that, in a region of interest, as much as 2 dB may be gained.
Many Reed-Solomon decoders, including the one decoding the outer code for Voyager data from Uranus, assume that all symbols have the same chance of being correct or incorrect. Insome cases, like in a burst of incorrect symbols, this is not the case, and a Reed-Solomon decoder could make use of this. The use of information about bit quality sent to the Reed-Solomon from an (inner) Viterbi decoder is examined, as well as information about the error status of adjacent symbols in decoding interleaved Reed-Solomon encoded symbols. It is discovered that, in a region of interest, only about 0.04 dB can gained.
Deep space missions choose a data rate to ensure reliable communication under most conditions. Certain critical data can be more heavily encoded, to be decoded under particularly bad atmospheric conditions. It is shown that, in such a system, finding and synchronizing critical data will not be a problem.