Dialog Semiconductor B.v.

Dialog Semiconductor (UK) Limited

Renesas Design Netherlands B.v.

Ashley Hughes

Wessel Harm Lubberhuizen

Paul Shields

Johannes Steensma

An active noise cancellation (ANC) system is presented. The ANC system includes a transducer; a first microphone; and a first adaptive filter coupled to a calculator. The calculator generates an error signal based on a difference between a filtered input signal and a signal from the first microphone. The filtered input signal is based on a first transfer function estimate of the transducer-to-first microphone transfer function via a first acoustic path. The calculator updates coefficients of the first adaptive filter using the error signal and generates with the first adaptive filter a first noise-cancellation signal.

Active noise cancellation system

A digital filter for filtering a pulse density modulation (PDM) signal is presented. The filter has a first filter circuit to receive an input signal and to provide a filtered input signal at successive time steps which include a first filtered value at the first time step and a second filtered value at a second time step. The filter also has a quantizer to provide an output signal comprising output values at successive time steps and a filter variable circuit with a first multiplication circuit to receive the first filter variable, and divide the first filter variable by a first gain factor and a first summing circuit configured to receive the divided first filter variable, receive the output signal, and add the divided first filter variable and the first output value and a second multiplication circuit and a delay circuit.

Digital filter

A digital filter structure and related method of digital filtering are presented. The digital filter structure is arranged to receive one or more clocked input signals having a first clock rate, and which is driven at a second clock rate higher than said first clock rate. The digital filter structure has a plurality of delay elements and multiplexing circuitry arranged to selectively engage the delay elements such that, at every clock cycle of the digital filter structure, a filter operation is performed on a different stream of data. The disclosure can be applied in many different contexts. One particular implementation example is that of an adaptive noise cancellation (ANC) system using sigma-delta infinite impulse response filters. In this context the present disclosure minimizes latency and hardware implementation area by requiring only one filtering circuit for multiple channels of data to be filtered.

Digital filter structure

An anti-noise signal generator and a method of generating an anti-noise signal are presented. The anti-noise generator includes a first microphone input to receive a first sigma-delta modulated signal at a microphone sampling frequency. The first microphone input is coupled to a combiner via a first path and a second path. The combiner is adapted to combine a first filtered signal from the first path and a second filtered signal from the second path to generate the anti-noise signal. The first path includes a first digital filter adapted to operate at a filter frequency equal or greater than the microphone sampling frequency. The second path includes a second digital filter. The first digital filter may be a sigma-delta based filter that includes a sigma-delta modulator.

Anti-noise signal generator

A signal processing structure and method are presented. A first digital filter operates on received sigma-delta modulated (SDM) input signals. A second pre-processing digital filter receives a SDM input signal, directly low pass filter the SDM input signal and provides an output SDM signal. The output sigma-delta modulated signal is provided as an input for said first digital filter. In standard digital systems operating with digital microphones, filtering of the microphones' output signal requires to first convert the signal into pulse code modulation (PCM), then filter and finally convert back to pulse density modulation (PDM). This approach increases the latency of the system because decimation and interpolation must be performed in order to pass from PDM to PCM. By using filters that operate directly on the oversampled PDM output of the digital microphones it is possible to reduce the latency of the system and minimize the hardware area.

Signal processing structure

A method of data calibration, and in particular sensor calibration, which involves gathering an initial first estimate and then binning the data samples, so that calibration can be performed without the need for a known reference stimulus. The present disclosure relates to calibration of vectors in a measurement system, and in particular to calibration of a correction function for systematic errors in successive data vectors. There is provided a method of determining a vector calibration function comprising: binning successive data vectors; and optimising the binned data vectors once data vectors allocated to a minimum number of unique bins have been observed. The method comprises establishing an initial calibration estimate and where the binning and optimising are performed based on said initial calibration estimate.

Calibration of vectors in a measurement system

A digital filter and a method for filtering a pulse density modulation (PDM) signal are presented. The digital filter has a first filter circuit to receive an input signal with input values at successive time steps to provide a filtered input signal with filtered values at successive time steps. The digital filter does not require sample-rate or data format conversions. Also, the digital filter is area and power efficient when implemented in hardware. Optionally, the digital filter has a sigma-delta modulator including the quantiser, the sigma-delta modulator being used to receive the filtered input signal and to process the filtered input signal before and/or after being quantised by the quantiser. This digital filter does not require sample-rate or data format conversions. This digital filter is area and power efficient when implemented in hardware.

A quantizer and a method for a sigma-delta modulator circuit that may be used as a component within an adaptive-noise cancelling headphone are presented. An apparatus includes a quantizer to receive an input signal with successive input values and quantizes the input signal at discrete intervals. This is done by mapping the input value of the input signal at each interval to one of a plurality of quantization levels with three or more quantization levels that are non-uniformly spaced. The plurality of quantization levels has a first portion with two or more quantization levels having the same sign and being proportional to a first fraction having one as its numerator and two to a power of a first variable as its denominator, the first variable being an integer and having a different value for each of the two or more quantization levels of the first portion.

Quantizer

A signal processor and a method for processing an input signal are presented. The signal processor is adapted to clip an oversampled input signal without introducing noise in the frequency band of interest. For instance, the signal processor may be used for clipping an acoustic signal. The signal processor includes a summer coupled to a limiter and to a feedback circuit. The summer is adapted to sum the input signal with at least one feedback signal to provide an adjusted signal. The limiter is adapted to compare the adjusted signal with a first threshold value and a second threshold value to provide a limited signal. The feedback circuit is adapted to calculate a difference between the limited signal and the adjusted signal, and to generate at least one feedback signal based on the difference.

Signal processor

The proposed invention implements real-time sensitivity estimation, using a microphone path, and variable gain. When a multi-microphone system is configured to perform in its target use case, and the microphone gain is estimated, and the system output is corrected for performance degradation, sensitivity compensation is performed. A classification system is implemented to enable or disable subsequent gain estimation, and hence power consumption required when enabled or disabled, on a frame-by-frame basis. An acoustic environment is used to trigger a classification system, with electrical power consumption analysis performed to detect audio segments. The approach to the microphone sensitivity mismatch problem is to estimate the mismatch at runtime and provide gain compensation, and provide runtime compensation for the difference in sensitivity to sound pressure level between transducer elements in an array of 2 or more microphones.

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Edinburgh, United Kingdom

Ashley Hughes