Allystar Lowest Power and Size Single-chip Dual-frequency RTK
Bibliographic record
Abstract
Until recently, using high precision GNSS was limited to applications that could afford the high cost, high power consumption and large size of geodetic GNSS receivers. In this context, the newly released Allystar HD9311 series GNSS receiver became a game changer. The receiver can provide dual-frequency RTK by using 3x3 mm GNSS SoC chip offered in Wafer-Level Chip-Scale Packaging (WLCSP), consuming only 35 mA @ 3.3V of power. This enables providing RTK for a wide range of applications, which cannot tolerate high cost and power consumption of geodetic receivers, such as smart phones, drones, autonomous driving and precision agriculture. To assist customers to integrate Allystar RTK chip solution into their products, Allystar has developed the TAU series module. The module has Allystar’s HD9311 chip integrated with a Temperature Compensated Crystal Oscillator (TCXO) and real-time clock. The size of the module is 7.60 x 7.60 mm2 Allystar is one of leading providers of multi-band GNSS chipsets to mass market. It was founded as a spin off from China Electronics Corporation (CEC) in 2016. Regardless of being a relatively new company, its employees have tens of years hands-on experience in GNSS research and development and its products are very mature. Allystar is an international company and has offices in Hong Kong, Calgary, Shenzhen, Beijing and Chengdu. Allystar solution can provide dual-frequency GNSS by using a single 3x3 mm2 chip without a need for external RF circuitry. This is a clear cost and power consumption advantage against competitors. Depending on the firmware used, Allystar hardware tracks GNSS signals in L1/L2, L1/L5 or L1/L6 frequency bands. Users can change the frequency band configuration easily by different firmware. The RTK engine runs on Allystar chip with no need for any external processor. Depending on the firmware, Allystar RTK engine is performed on either GPS L1/L5 and GALILEO E1/E5a, GPS L1/L2C and BeiDou B1I/B2I, GPS L1/L2C and GLONASS L1OF/L2OF or GPS L1/L5 and BeiDou B1I/B2a signals. While GPS/Galileo is a more suitable configuration to be used outside Asia, GPS/BEIDOU provides an improved solution inside Asia, where users can more easily track BeiDou IGSO and GEO satellites. The RTK engine can also support additional signals such as BeiDou-3 B1C in the future when the signals will commonly be available at RTK base-stations. Allystar RTK engine supports corrections in RTCM3 MSM format that are provided by most RTK service providers in the world. In this article, Allystar RTK engine is tested in both static and kinematics environments. The high reliability and low wrong fixing rate of Allystar RTK engine is demonstrated. Reliable RTK solution is one of key requirement on autonomous applications. For Allystar receivers, it is shown that wrong fixing rate in challenging environments is significantly lower than that of the competitors. Low wrong fixing rate is achieved by advanced Allystar RTK ambiguity validation methods and excellent observation quality considering the low power consumption and small chip size. As a summary, it is demonstrated that Allystar RTK engine running on HD9311 chip is the most competitive RTK solution in the market. It can provide better reliability than the solutions with much larger size and more expensive cost. Also, overall RTK ambiguity fixing rate and solution accuracy are comparable to the competitors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".