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Step 1: Inventory the file before decoding anything
Septentrio Binary Format (SBF) is organized as binary blocks, and block versions can differ. A file with an .sbf extension is therefore not guaranteed to work with any given parser. Before analysis, find out which block types the file contains, how many records of each, and their effective rate. Septentrio’s SBF Analyzer (part of RxTools) can inspect file contents and show message statistics. Its support material gives an example of counting PVTGeodetic records. Use it as an independent check on whatever your Python code reports.
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Sparse records are not automatically data loss. Septentrio documents interval-based output and OnChange output, and some blocks can only be emitted at their natural renewal rate. Check the block inventory and the configured output setup before calling a gap a drop.
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The script below uses only the standard library. It follows the SBF frame layout as I know it from Septentrio’s reference guides: a $@ sync, a CRC-16, a 16-bit ID field (block number in the low 13 bits, revision in the top 3), a length, then a payload that starts with TOW (ms) and week number. Confirm these details against the reference guide for your firmware before relying on the output.
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import struct
from collections import Counter
def crc16(data, crc=0):
# CRC-CCITT, polynomial 0x1021, initial value 0
for b in data:
crc ^= b << 8
for _ in range(8):
crc = ((crc << 1) ^ 0x1021) & 0xFFFF if crc & 0x8000 else (crc << 1) & 0xFFFF
return crc
def iter_blocks(path):
buf = open(path, "rb").read()
i, n = 0, len(buf)
while True:
i = buf.find(b"$@", i)
if i < 0 or i + 8 > n:
return
crc, bid, length = struct.unpack_from("<HHH", buf, i + 2)
if length < 8 or length % 4 or i + length > n:
i += 2; continue
ok = crc16(buf[i + 4:i + length]) == crc
if not ok:
i += 2; continue
yield bid & 0x1FFF, bid >> 13, i, buf[i:i + length]
i += length
if __name__ == "__main__":
import sys
counts = Counter()
for num, rev, off, blk in iter_blocks(sys.argv[1]):
counts[(num, rev)] += 1
for (num, rev), c in sorted(counts.items()):
print(f"block {num} rev {rev}: {c}")The output lists each block number with its revision, which is exactly what you need to compare against a parser’s supported versions. Records that fail CRC are skipped here; counting them separately is worthwhile, because a file with many CRC failures points to a recording or transfer problem rather than a GNSS one.
Step 2: Choose a decoder and verify its version support
Septentrio’s community listing links Python SBF parser projects. The SBF Parser repository describes parsing streams and files into JSON structures. Treat any such project as a candidate, not a given: check its supported block IDs and revisions against your inventory, and check the current release and firmware range yourself. Compatibility for your receiver and parser pairing cannot be assumed.
| Axis | What to check |
|---|---|
| Block and version support | Does it decode the block numbers and revisions in your inventory? |
| Input shape | Files, live streams, or both. The SBF Parser project describes both. |
| Output form | Structured JSON for analysis code, or a conversion route. Septentrio’s SBF Converter outputs include RINEX, KML, GPX and ASCII. |
| Validation | Can you compare record counts and values with SBF Analyzer? |
| Maintenance | Release date, receiver generation and firmware range. |
For a narrow task such as PVT mode over time, writing the few fields you need yourself, as below, is a reasonable alternative to a full decoder. Use a library when you need measurement-level blocks such as MeasEpoch or MeasExtra, which need a more involved decoder.
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Step 3: Build a time-indexed PVT table
RTK absolute position is reported in PVTCartesian or PVTGeodetic, while the baseline vector is reported in BaseVectorCart or BaseVectorGeod (AsteRx SB3 Pro+ reference guide). Which are present depends on the logged blocks and configuration, so do not assume both coordinate systems exist. A baseline vector is relative to the base and is not an absolute coordinate.
The header of a PVTGeodetic block, as I understand the layout, carries TOW and week number followed by a Mode byte and an Error byte. The low four bits of Mode hold the PVT type, and the upper bits hold flags. Verify the mapping in your receiver’s reference guide. Commonly documented values include 1 stand-alone, 2 differential, 4 RTK fixed and 5 RTK float.
import pandas as pd
MODES = {0: "no solution", 1: "standalone", 2: "differential",
3: "fixed location", 4: "RTK fixed", 5: "RTK float"}
DNU = 4294967295 # TOW do-not-use value
rows = []
for num, rev, off, blk in iter_blocks(path):
if num == 4007: # PVTGeodetic
tow, wnc, mode, err = struct.unpack_from("<IHBB", blk, 8)
if tow != DNU:
rows.append((wnc, tow, mode & 0x0F, err, rev))
pvt = pd.DataFrame(rows, columns=["wnc", "tow_ms", "type", "error", "rev"])
pvt["t"] = pvt.wnc * 604800.0 + pvt.tow_ms / 1000.0 # seconds since GPS week 0
pvt["state"] = pvt.type.map(MODES).fillna("other (" + pvt.type.astype(str) + ")")Keep the raw week, TOW and block revision columns next to any normalized time. If a file has mixed rates or more than one time scale, write down your normalization policy instead of silently interpolating.
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Step 4: Quantify fix quality
With the table, summarize what the receiver reported: time share per state, number of fixed-to-float transitions, and the duration of each non-fixed stretch.
pvt = pvt.sort_values("t").reset_index(drop=True)
share = pvt.state.value_counts(normalize=True)
pvt["run"] = (pvt.state != pvt.state.shift()).cumsum()
runs = (pvt.groupby("run")
.agg(state=("state", "first"), start=("t", "first"), end=("t", "last"), n=("t", "size")))
runs["duration_s"] = runs.end - runs.start
drops = runs[(runs.state != "RTK fixed") & (runs.index > runs.index.min())]Compute durations from epoch timestamps rather than record counts, because the logging interval may differ between files. Also look at the spacing between consecutive PVT records: gaps much larger than the configured interval are a different phenomenon from a state change, and may reflect output configuration or recording problems.
Step 5: Overlay correction and status records
Septentrio’s documented block families give you the context to correlate against the PVT timeline:
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- DiffCorr group: DiffCorrIn, BaseStation, RTCMDatum. Use what is present and interpretable in your file.
- Status group: ReceiverStatus, InputLink, NTRIPClientStatus, OutputLink.
- PVTExtra group: DOP, PVTSatCartesian, PVTResiduals, RAIMStatistics, for geometry and residual context.
- Measurement blocks: MeasEpoch, MeasExtra, for signal-level work.
None of these is guaranteed to be in a given log. If DiffCorrIn was never enabled, you cannot say whether corrections stopped arriving. That limit is itself a finding. Plot position-state, correction arrival times and any status changes on one shared time axis, using the same time conversion for every block.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Step 6: Reading a fixed-to-float transition
In the AsteRx SB3 Pro+ firmware 4.10.1 reference guide, RTK fixed means the carrier-phase integer ambiguities are resolved. Float means they are still floating. The guide says low data availability, such as a low satellite count, or insufficient measurement quality, such as high multipath, can leave ambiguities floating, and that float solutions improve as they converge over time. Septentrio’s online RTK explainer adds signal quality, correction reliability, obstruction and RF interference as factors in achieving or keeping a fixed solution. Its performance figures are vendor-described typical values, not guarantees for your data.
Those are candidate explanations, not diagnoses. The table below pairs a log observation with what it can and cannot support.
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| Observation in the log | Supports | Does not prove |
|---|---|---|
| DiffCorrIn records stop or become sparse shortly before the move to float | A correction-supply problem is plausible | Where the interruption occurred (base, network, link, receiver input) |
| Corrections continue arriving through the transition | Makes a pure correction outage less likely | That the corrections were good quality or from a nearby enough base |
| NTRIPClientStatus or InputLink changes at the same time | A connection-level event is plausible | Which side caused it |
| Rising DOP or a falling satellite count (if logged) | Geometry or availability degradation | Obstruction as the physical cause |
| Degradation only while the receiver is in a particular location or motion state | Environment-related causes, such as obstruction or multipath | Multipath specifically, without measurement-level evidence or site knowledge |
Write findings in two parts: first the observation (“fixed to float at 14:03:22 GPS time, float for 41 s, corrections logged throughout”), then the hypotheses ranked by supporting evidence. Do not claim an obstruction, interference or multipath event unless the logged evidence or independent site information supports it. After the transition, expect a float period before fixed returns, since float convergence takes time.
Step 7: Validate against the vendor tools and configuration
- Compare your PVTGeodetic count with SBF Analyzer’s message statistics for the same file.
- Confirm the receiver model and firmware. The cited guide is specific to AsteRx SB3 Pro+ firmware 4.10.1, so consult the reference guide for your own receiver for field layouts and mode definitions.
- Check the logging configuration (output groups and intervals) before treating a missing block type as loss.
- For a quick conversion route, SBF Converter can export RINEX, KML, GPX and ASCII, which is handy for a sanity check in other tools.
Septentrio’s Post Processing SDK manual (version 4.6.5) says: “The benefit of SBF is its compactness.” It recommends the format for processing detailed receiver information. The compactness is why a log answers many questions and still leaves some open when blocks were not enabled.
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