Patent Description:
Vehicle radio receivers which are part of car infotainment systems suffer from degraded analog and digital radio reception quality due to electrical motor interference. This is particularly a concern for AM radio, which is the only available radio medium to cover significant distance in many large countries such as the US, Japan, India and Australia. Other radio standards suffer as well due to increasing drive voltage and inverter switching frequencies, these are driven by efficiency improvements that improve switching losses by decreasing the switching time. <CIT> describes methods and systems for estimation and mitigation of swept-tone interferers. <CIT> describes an orthogonal frequency division multiplexing receiver capable of cancelling pulse interference.

Various aspects of the disclosure are defined in the accompanying claims. In a first aspect there is provided a method of signal processing for a radio receiver according to claim <NUM>.

In a second aspect, there is provided a non-transitory computer readable media comprising a computer program comprising computer executable instructions according to claim <NUM>.

In a third aspect, there is provided a signal processor for a radio receiver according to claim <NUM>.

In one or more embodiments, the signal processor may further comprise a frequency estimator having a frequency estimator input coupled to the signal input, and a frequency estimator output coupled to the second synthesizer input, and configured to estimate the frequency domain spectral repetition interval of a frequency magnitude spectrum of the received signal. Further refinements are defined by the dependent claims.

In the figures and description like reference numerals refer to like features. Embodiments are now described in detail, by way of example only, illustrated by the accompanying drawings in which:.

<FIG> shows a signal processor <NUM> for a radio receiver according to an embodiment. The signal processor <NUM> may also be referred to as an interference removal processor. The signal processor <NUM> may have a signal input <NUM>, a interferer repetition interval input <NUM> and a signal processor output <NUM>. The operation of the signal processor <NUM> is illustrated in <FIG> which shows a method of signal processing <NUM> for a radio receiver. In step <NUM>, a signal may be received at the signal input <NUM> by a radio receiver for example an AM, FM, or other audio broadcast radio signal. In step <NUM> a spectral repetition interval value of an interference signal may be received on the interferer repetition interval <NUM>. This spectral repetition interval value may for example correspond to a frequency value between peaks in a frequency spectrum of an interferer with a quasi-repetitive frequency spectrum. An example interferer with a quasi-repetitive frequency spectrum may be for example interference from an electric motor driven by a an inverter controlled PWM control signal. In this example the spectral repetition interval value may correspond to the frequency of the inverter control signal. In step <NUM>, an interference reference signal may be generated based on the spectral repetition interval value which may be used to determine which frequencies in the input signal are likely to be noise and which frequencies are due to the audio signals broadcast to the radio receiver. In step <NUM>, the signal may be adapted dependent on the generated interference reference signal. In some examples, the signal may be adapted by subtracting the generated interference reference signal from the original received signal.

In some examples, the signal may be adapted by muting the received signal for example by setting the signal magnitude values to zero at one or more times corresponding to peaks of the generated interference reference signal. In this example, packet loss concealment techniques may also be used for example as described in <NPL>.

In an example, some interference sources may have a quasi-repetitive frequency spectrum. One example of such an interferer is an electric motor which is driven by an inverter. The resulting interference source may have a quasi-repetitive frequency spectrum corresponding to the inverter switching frequency. This quasi-repetitive frequency spectrum may be used to generate a model of the interferer signal which may then be used to adapt received signal to improve the signal to noise ratio.

For example in vehicles, for efficiency reasons, pulse-width modulation (PWM) switching is used in many power transmission systems within a vehicle, including the main traction, mirror, wiper, window, seat and air conditioning motors. This method produces a characteristic interference spectrum. Other interference sources can include, but are not limited to, inverters for lighting, DC/DC conversion and plug in or wireless charging. In addition, for electric vehicles (EV) the traction motors, which may number up to <NUM> or more, each employ an inverter to convert a DC voltage to sinusoidal like waveforms to drive each motor. The inverter switches up to <NUM> V DC at its input to create a <NUM>-phase sinusoidal like output waveform, the control inputs to the inverter are rotation frequency and output amplitude. The switching frequency can be constant or variable, and is typically orders of magnitude higher than the rotation frequency.

The typically used PWM sinusoidal switching scheme produces a quasi-repetitive spectrum with each repetition spaced at (sub-) intervals of the switching frequency with side-bands at multiples of the rotation frequency.

<FIG> shows a signal processor or interference removal processor <NUM> for a radio receiver according to an embodiment. A signal input <NUM> may be connected to a first synthesizer input of an interference synthesizer <NUM>. The interference synthesizer <NUM> may also have a second synthesizer input <NUM>. An interference synthesizer output <NUM> may be connected to a first adder input of an adder <NUM>. The second adder input of adder <NUM> may be connected to the signal input <NUM>. An adder output of the adder <NUM> may be connected to the signal processor output <NUM>.

In operation, the signal processor <NUM> may receive a signal on the signal input <NUM>. The signal may for example be derived from a radio signal such as an AM signal, FM signal or DAB signal. The signal may be the original antenna signal or a complex-valued IF signal in a frequency range of interest. The interference synthesizer <NUM> may receive a value corresponding to the inverter switching frequency of an electric motor on the second synthesizer input <NUM>. Examples of interference sources for radio signals may for example be interference due to the operation of an electric motor driven by an inverter. The switching frequency of the inverter may be correlated to the frequency of the resulting electrical interference signal due to the electric motor resulting in the interferer having a predictable spectral repetition interval. This information may be used by the interference synthesizer <NUM> to generate an interference reference signal on the interference synthesizer output <NUM>. This interference reference signal may then be subtracted from the original input signal by the adder <NUM>. The resulting signal may be output from the adder <NUM> to the signal processor output <NUM>. The input signal bandwidth may be a multiple of the inverter switching frequency in order improve the accuracy of the interference model.

<FIG> shows a method of signal processing <NUM> for a radio receiver. In step <NUM>, a signal may be received by a radio receiver for example an AM, FM, or other audio broadcast radio signal. In step <NUM> a spectral repetition interval value of an interference signal may be received. In step <NUM>, an interference reference signal may be generated based on the interferer frequency value which may be used to determine which frequencies in the input signal are likely to be noise and which frequencies are due to the audio signals broadcast to the radio receiver. In step <NUM>, the interference reference signal generated in step <NUM> may be subtracted from the original received signal.

<FIG> shows a signal processor <NUM> for a radio receiver according to an embodiment. A signal input <NUM> may be connected to a first input of an interference synthesizer <NUM>. The interference synthesizer <NUM> may also have a second input <NUM> connected to a frequency estimator output of an interferer frequency estimator <NUM>. A frequency estimator input of the interferer frequency estimator <NUM> may be connected to the signal input <NUM>. An interference synthesizer output <NUM> may be connected to a first input of an adder <NUM>. The second input of adder <NUM> may be connected to the signal input <NUM>. An output of the adder <NUM> may be connected to the signal processor output <NUM>.

In operation, the signal processor <NUM> may receive a signal on the signal input <NUM>. The interference synthesizer <NUM> may receive a spectral repetition interval value corresponding to the expected frequency of an interference source which may be an estimated frequency determined by interferer frequency estimator <NUM>. The estimated frequency may be used by the interference synthesizer <NUM> to generate an interference reference signal on the interference synthesizer output <NUM>. The interference reference signal may then be subtracted from the original input signal by the adder <NUM>. The resulting signal may be output from the adder <NUM> to the signal processor output <NUM>.

In an example, the quasi-repetitive nature of the interference spectrum described earlier can be exploited to model the interference spectrum even in the presence of other spectrum components such as AM signals, etc. The signal processors <NUM>, <NUM>, <NUM> may denoise an RF signal corrupted for example by EV traction and other PWM based inverter interferences. The inverter switching frequency may be used to synthesise the interference from an average of the interference spectral repetitions. The synthesised interference reference is then subtracted from the input signal in the time or frequency domain. In some examples for AM radio reception the interference reduction may be <NUM> dB.

Prior methods may for example suppress the main AM carriers from the input IF signal to improve the time domain detection of interferences. In the case of strong AM stations, not only are the carriers but also the side-bands hamper detecting interferences such as pulses with time domain pulse detection. Suppressing the complete side-band frequency range would therefore be required, e.g. by notch-filtering the AM bands with a bandwidth of <NUM> centred around each carrier. In this case not only the AM signals would be suppressed, but also the frequency components of the interference located within the suppressed AM bands. Consequently, the remaining time domain pulse interference would no longer be representative of the actual pulse interference, and the EV noise suppression performance would be greatly impaired.

Suppressing all dominant frequency components of the RF input signal (including low rate FSK, digital radio, FM, continuous tones and random walk tones) in order to improve the time domain detection of the interference pulses may lead to the undesired suppression of many interference frequency components, and hence, corrupt the time domain estimate of the interference. By generating an interference reference signal based on identifying the spectral repetition interval of a likely interferer, suppression of interference due to pulses may be improved.

<FIG> shows an example spectrogram <NUM> for AM radio reception of an input signal with frequency on the x-axis ranging between -<NUM> and + <NUM> and time on the y-axis, ranging from <NUM> to <NUM> seconds. The example input signal includes a desired AM radio station <NUM> centred nominally at <NUM>, and an adjacent AM radio station <NUM> centred nominally at -<NUM>. An example interference <NUM> may be caused by an electric motor powering a vehicle. The first spectrogram <NUM> shows the situation with interference. The second spectrogram <NUM> shows the result after de-noising for example using signal processors <NUM>,<NUM>,<NUM> or methods <NUM>,<NUM>.

<FIG> shows a method <NUM> of estimating the interferer spectrum repetition interval. The method <NUM> may be used for example to implement the interferer frequency estimator <NUM>. In step <NUM>, the auto-correlation function of the magnitude spectrum of the input signal may be determined. In step <NUM>, a peak value of the auto-correlation may be determined. In step <NUM>, an interferer frequency may be estimated from the non-zero lag peak values of the first-order difference of the auto-correlation.

In an example, an interferer source such as a motor driven by an inverter can have a switching frequency estimated by tracking the frequency domain period of the repeating interference patterns. This switching frequency may correspond to the spectrum repetition interval of an interferer signal. This estimation may for example include processing the auto-correlation function of the input signal frequency magnitude spectrum. Since the expected interference pattern is quasi or loosely replicated across the frequency magnitude spectrum, the second peak in the autocorrelation function indicates the distance between repetitions, which corresponds to the inverter switching frequency.

<FIG> shows the autocorrelation function <NUM> at a given time segment. The frequency between -<NUM> to +<NUM> is on the x-axis. The normalised correlation value is plotted on the y-axis It can be observed that there are many peaks <NUM> outside the central region <NUM>, which may be used to determine the inverter frequency. <FIG> shows the first-order difference <NUM> of the auto-correlation function. The largest peak <NUM> outside a central region of for example, +/-<NUM> corresponds to the inverter frequency of <NUM>. This peak may be tracked over time to cope with a changing inverter frequency, and may also render the estimate more robust, if the inverter frequency changes slowly over time.

<FIG> shows an interference synthesizer <NUM> which may be used to implement the interference synthesizers <NUM>, <NUM>. Interference synthesizer <NUM> includes a fast Fourier transform (FFT) module <NUM>, a reshaper module <NUM>, an analyser module <NUM>, a replicator module <NUM>, a combiner module <NUM> and an inverse FFT module <NUM>. In other examples other frequency-to-time and time-to-frequency modules may be used instead of FFT module <NUM> and iFFT module <NUM> such as for example, other Fourier transform methods or wavelet transforms. In some examples, the frequency-to-time and time-to-frequency modules may also include windowing and overlap-add functions. The FFT module <NUM> has an FFT input coupled to the interference synthesizer input <NUM>. The FFT module has an FFT magnitude output <NUM> and an FFT phase output <NUM>. The FFT magnitude output <NUM> may be connected to a first reshaper input of the reshaper module <NUM> and a first combiner input of the combiner module <NUM>.

The reshaper module <NUM> has a second reshaper input <NUM> for receiving an interferer frequency value. The reshaper module <NUM> has a reshaper output <NUM> connected to an analyser input of the analyser module <NUM>. The analyser module <NUM> has a first analyser output <NUM> connected to a replicator input of the replicator module <NUM>. The analyser module <NUM> has a second analyser output <NUM> connected to a second combiner input of the combiner module <NUM>. A replicator output <NUM> may be connected to a third combiner input of the combiner module <NUM>. A combiner output <NUM> may be connected to a first iFFT input of inverse FFT module <NUM>. A second iFFT input of the inverse FFT module <NUM> may be connected to the FFT phase output <NUM>. The combiner output may be connected to the interference synthesizer output <NUM>.

The interference synthesizer <NUM> obtains an interference model reference by exploiting the quasi-repetitive nature of the spectrum. In operation, an input signal may be received at interference synthesizer input <NUM>. The frequency magnitude spectrum may be determined by the FFT module <NUM>. The frequency magnitude spectrum is output on FFT magnitude output <NUM>.

The reshaper module <NUM> may reshape the frequency magnitude spectrum into frames of length Finv, where Finv is the interferer spectrum repetition interval and the frames are normalised to account for possible spectrum level variations. For example for a received signal spectrum including <NUM> frequency bins, the FFT domain may be split into frames of <NUM> bins where <NUM> bins corresponds to the spectrum repetition interval of the interferer. The interference is considered a cyclo-stationary process in the FFT domain which may allow a statistical separation between the interference and a wanted signal such as the AM radio signal. In some examples, the normalisation factor can be determined based on the peak value in the frame, or on the average power in the frame. In some examples, the normalisation factor can be determined based on the magnitude at the expected peak position which is known from the peak bin position in the across-frame average (without normalisation).

The normalised frames may be output from the reshaper module <NUM> and then statistically analysed by the analyser module <NUM> which may output an interference model frame on the first analyser output <NUM> and, optionally, a signal mask on second analyser output <NUM> that reflects the probability that a given frequency bin contains only the interference.

The analyser module <NUM> may determine the interference model frame from the separate normalised frames (and optionally, from the frames of a number of past time segments) as the expected magnitude for each frequency bin in the interference model frame. This may be done for example by determining an average value for bin0 in frame0, bin0 in frame1, bin0 in frame <NUM> and so on. Alternatively or in addition, in other examples a median value may be determined.

The analyser module <NUM> may determine the expected variability for each bin in the interference model frame, for example as the standard deviation across frames. This allows for the generation of a signal mask which assigns a determined frequency bin mask value between zero and unity to each frequency bin. In some examples, the signal mask may be zero if it originates from the interference, for example if the (normalised) magnitude of a bin falls within the expected range, for example within <NUM> standard deviation of the corresponding bin in the interference model, and it is unity if it does not originate within the expected range. In other examples a value between <NUM> and <NUM> may be used. The signal mask may be considered as a weighting factor for each respective frequency bin. The signal mask may be output on the second analyser output <NUM>. In other examples, other measures of variability may be used such as median absolute deviation.

The interference model frame consists of a frequency magnitude spectrum and may then be replicated across the entire spectrum by replicator module <NUM> resulting in an extended interference reference model. For example for an interference model frame of <NUM> bins replicated <NUM> times. The replicator module <NUM> may scale (de-normalise) each segment, i.e. each replicated interference model frame to the original power. The replicator module <NUM> may output an extended interference model frequency magnitude spectrum on replicator output <NUM>.

The combiner module <NUM> may combine the extended interference model spectrum with the original magnitude spectrum on the basis of the signal mask. For example the original magnitude spectrum may be compared with the statistics repeated vector and a decision is made whether a certain bin is interference or not based on the comparison. The values in the original magnitude spectrum deemed not to be interference may be cancelled out in frequency domain by setting them to zero, or by setting them to the corresponding values in the extended interference model spectrum.

The resulting modified extended interference model magnitude spectrum is then considered to be a model of the interference spectrum and is output on the combiner output <NUM>. The inverse FFT module <NUM> may then apply an inverse FFT to the model of the interference spectrum together with the phase information of the original received signal to convert back into the time domain. The resulting signal is an interferer reference signal which is added to the input signal to remove the interference from the input signal as described in <FIG>, <FIG>.

In some examples the model of the interference signal and may be subtracted from the original signal in the frequency domain by a subtractor before converting back to the time domain. In this case, the inverse FFT module may be omitted from the interference synthesizer.

In some examples, the time domain interference model reference may be further processed by a peak detector (not shown) to only keep the peak values and neighbouring time samples to form the interference reference. For example a sample may be labelled as a pulse when its magnitude exceeds a threshold value. This threshold value can be fixed, or it can be a function of the signal dynamics.

In some examples the interference synthesizer may process signals in consecutive or overlapping time domain frames. In case of a time-varying inverter switching frequency, each time domain frame may have a different interferer frequency value. The further generated interferer reference signal may then be subtracted from the input signal as previously described.

<FIG> shows a method of interference reference signal generation <NUM>. In step <NUM>, an input signal is received. In step <NUM> an FFT is applied to the input signal. In step <NUM>, the frequency range may be divided into frames determined by an interferer frequency which may be a fixed value or a value estimated from the input signal. In step <NUM> the magnitude values for each frequency bin may be normalized (per frame).

In step <NUM> the average bin value across frames for each frame bin may be determined. The standard deviation for each frame bin may be determined in step <NUM>. In step <NUM> the average bin value for each frame bin may be used to construct an interference model frame. In step <NUM>, the interference model may be replicated across the frequency spectrum i.e. for a number of frames corresponding to the number of frames in step <NUM>. In step <NUM> the received signal FFT spectrum may be compared with the replicated interference model for example based on the standard deviation value for each bin. In step <NUM>, the signal FFT spectrum may be modified by cancelling the bin values in the signal FFT spectrum which are not interference. In step <NUM> an inverse FFT may be applied to the modified signal FFT spectrum.

A signal processor and method of signal processing for a radio receiver is described. An input signal is received together with a spectral repetition interval value of an interferer signal. An interference reference signal is generated from the received spectral repetition interval value and the received signal. The received signal is adapted using the generated interference reference signal.

Claim 1:
A method (<NUM>) of signal processing for a radio receiver, the method comprising:
receiving a signal (<NUM>);
receiving a spectral repetition interval value of an interferer signal (<NUM>);
generating an interference reference signal from the received spectral repetition interval value and the received signal (<NUM>); and
adapting the received signal by adding the received signal and the interference reference signal or subtracting the interference reference signal (<NUM>) from the received signal;
wherein generating the interference reference signal further comprises:
applying a time-to-frequency transform (<NUM>) to generate a frequency magnitude spectrum of the received signal;
splitting the received signal frequency magnitude spectrum into a plurality of frames (<NUM>), each frame of length Finv, where Finv is the spectral repetition interval of the interferer signal;
normalizing (<NUM>) a magnitude value of each frequency bin in each frame of the plurality of frames;
determining an interference model frame (<NUM>) from the plurality of frames;
generating an extended interference reference model by replicating the interference model frame (<NUM>) by a number equal to the number of the plurality of frames (<NUM>) and de-normalizing each replicated interference model frame;
comparing (<NUM>) the frequency bins of the extended interference reference model and the frequency bins of the received signal frequency magnitude spectrum to determine which frequency bins include interference;
modifying (<NUM>) the extended interference reference model dependent on the comparison; and
generating the interference reference signal from the modified extended interference reference model.