Finite precision arithmetic in Polyphase Filterbank implementations
- Authors: Myburgh, Talon
- Date: 2020
- Subjects: Radio interferometers , Interferometry , Radio telescopes , Gate array circuits , Floating-point arithmetic , Python (Computer program language) , Polyphase Filterbank , Finite precision arithmetic , MeerKAT
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/146187 , vital:38503
- Description: The MeerKAT is the most sensitive radio telescope in its class, and it is important that systematic effects do not limit the dynamic range of the instrument, preventing this sensitivity from being harnessed for deep integrations. During commissioning, spurious artefacts were noted in the MeerKAT passband and the root cause was attributed to systematic errors in the digital signal path. Finite precision arithmetic used by the Polyphase Filterbank (PFB) was one of the main factors contributing to the spurious responses, together with bugs in the firmware. This thesis describes a software PFB simulator that was built to mimic the MeerKAT PFB and allow investigation into the origin and mitigation of the effects seen on the telescope. This simulator was used to investigate the effects in signal integrity of various rounding techniques, overflow strategies and dual polarisation processing in the PFB. Using the simulator to investigate a number of different signal levels, bit-width and algorithmic scenarios, it gave insight into how the periodic dips occurring in the MeerKAT passband were the result of the implementation using an inappropriate rounding strategy. It further indicated how to select the best strategy for preventing overflow while maintaining high quantization effciency in the FFT. This practice of simulating the design behaviour in the PFB independently of the tools used to design the DSP firmware, is a step towards an end-to-end simulation of the MeerKAT system (or any radio telescope using nite precision digital signal processing systems). This would be useful for design, diagnostics, signal analysis and prototyping of the overall instrument.
- Full Text:
- Authors: Myburgh, Talon
- Date: 2020
- Subjects: Radio interferometers , Interferometry , Radio telescopes , Gate array circuits , Floating-point arithmetic , Python (Computer program language) , Polyphase Filterbank , Finite precision arithmetic , MeerKAT
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/146187 , vital:38503
- Description: The MeerKAT is the most sensitive radio telescope in its class, and it is important that systematic effects do not limit the dynamic range of the instrument, preventing this sensitivity from being harnessed for deep integrations. During commissioning, spurious artefacts were noted in the MeerKAT passband and the root cause was attributed to systematic errors in the digital signal path. Finite precision arithmetic used by the Polyphase Filterbank (PFB) was one of the main factors contributing to the spurious responses, together with bugs in the firmware. This thesis describes a software PFB simulator that was built to mimic the MeerKAT PFB and allow investigation into the origin and mitigation of the effects seen on the telescope. This simulator was used to investigate the effects in signal integrity of various rounding techniques, overflow strategies and dual polarisation processing in the PFB. Using the simulator to investigate a number of different signal levels, bit-width and algorithmic scenarios, it gave insight into how the periodic dips occurring in the MeerKAT passband were the result of the implementation using an inappropriate rounding strategy. It further indicated how to select the best strategy for preventing overflow while maintaining high quantization effciency in the FFT. This practice of simulating the design behaviour in the PFB independently of the tools used to design the DSP firmware, is a step towards an end-to-end simulation of the MeerKAT system (or any radio telescope using nite precision digital signal processing systems). This would be useful for design, diagnostics, signal analysis and prototyping of the overall instrument.
- Full Text:
CubiCal: a fast radio interferometric calibration suite exploiting complex optimisation
- Authors: Kenyon, Jonathan
- Date: 2019
- Subjects: Interferometry , Radio astronomy , Python (Computer program language) , Square Kilometre Array (Project)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/92341 , vital:30711
- Description: The advent of the Square Kilometre Array and its precursors marks the start of an exciting era for radio interferometry. However, with new instruments producing unprecedented quantities of data, many existing calibration algorithms and implementations will be hard-pressed to keep up. Fortunately, it has recently been shown that the radio interferometric calibration problem can be expressed concisely using the ideas of complex optimisation. The resulting framework exposes properties of the calibration problem which can be exploited to accelerate traditional non-linear least squares algorithms. We extend the existing work on the topic by considering the more general problem of calibrating a Jones chain: the product of several unknown gain terms. We also derive specialised solvers for performing phase-only, delay and pointing error calibration. In doing so, we devise a method for determining update rules for arbitrary, real-valued parametrisations of a complex gain. The solvers are implemented in an optimised Python package called CubiCal. CubiCal makes use of Cython to generate fast C and C++ routines for performing computationally demanding tasks whilst leveraging multiprocessing and shared memory to take advantage of modern, parallel hardware. The package is fully compatible with the measurement set, the most common format for interferometer data, and is well integrated with Montblanc - a third party package which implements optimised model visibility prediction. CubiCal's calibration routines are applied successfully to both simulated and real data for the field surrounding source 3C147. These tests include direction-independent and direction dependent calibration, as well as tests of the specialised solvers. Finally, we conduct extensive performance benchmarks and verify that CubiCal convincingly outperforms its most comparable competitor.
- Full Text:
- Authors: Kenyon, Jonathan
- Date: 2019
- Subjects: Interferometry , Radio astronomy , Python (Computer program language) , Square Kilometre Array (Project)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/92341 , vital:30711
- Description: The advent of the Square Kilometre Array and its precursors marks the start of an exciting era for radio interferometry. However, with new instruments producing unprecedented quantities of data, many existing calibration algorithms and implementations will be hard-pressed to keep up. Fortunately, it has recently been shown that the radio interferometric calibration problem can be expressed concisely using the ideas of complex optimisation. The resulting framework exposes properties of the calibration problem which can be exploited to accelerate traditional non-linear least squares algorithms. We extend the existing work on the topic by considering the more general problem of calibrating a Jones chain: the product of several unknown gain terms. We also derive specialised solvers for performing phase-only, delay and pointing error calibration. In doing so, we devise a method for determining update rules for arbitrary, real-valued parametrisations of a complex gain. The solvers are implemented in an optimised Python package called CubiCal. CubiCal makes use of Cython to generate fast C and C++ routines for performing computationally demanding tasks whilst leveraging multiprocessing and shared memory to take advantage of modern, parallel hardware. The package is fully compatible with the measurement set, the most common format for interferometer data, and is well integrated with Montblanc - a third party package which implements optimised model visibility prediction. CubiCal's calibration routines are applied successfully to both simulated and real data for the field surrounding source 3C147. These tests include direction-independent and direction dependent calibration, as well as tests of the specialised solvers. Finally, we conduct extensive performance benchmarks and verify that CubiCal convincingly outperforms its most comparable competitor.
- Full Text:
- «
- ‹
- 1
- ›
- »