Portions of this document are subject to copyright protection. The copyright owner does not object to facsimile reproduction of the patent document as it is made available by the U.S. Patent and Trademark Office. However, the copyright owner reserves all copyrights in the software described herein and shown in the text and drawings. The following notice applies to the software described and illustrated herein: Copyright © 2010, Robert Bosch GmbH, All Rights Reserved.
1. Field of the Invention
The present invention relates to finite impulse response (FIR) filters and, more particularly, to FIR filters as they are applied to audio loudspeakers or other devices having a frequency response.
2. Description of the Related Art
An FIR type of digital filter has a finite impulse response in that it approaches zero in a finite number of sample intervals. In contrast, an infinite impulse response (IIR) filter has internal feedback and may continue to respond indefinitely. FIR filters have several advantages over IIR filters, including being inherently stable, requiring no feedback, and being capable of being linear or complex phase.
A basic form of an FIR filter may be provided by the following difference polynomial equation which defines how the input signal x[n] is related to the output signal y[n]:
y[n]=b
0
x[n]+b
1
x[n−1]+ . . . +bNx[n−N]
wherein bi are the filter coefficients. N is known as the “filter order.” An Nth-order filter has (N+1) terms on the right-hand side.
Another possible approach to defining the order of a polynomial is that the order is the highest order power in the polynomial, or alternatively, the polynomial's polynomial degree. For example, the polynomial P(x)=anxn+ . . . +a2x2+a1x+a0 is of order n, wherein n is greater than two (two being the highest other power of x that is shown in the equation).
FIR filters, because of their finite length, may exhibit problems correcting magnitude and phase at low frequencies, such as below 300 Hz. The frequency at which the FIR filter loses resolution is a function of the DSP sampling rate and the FIR filter order. This is related to the time-frequency uncertainty principle Δt·Δf=1 where Δt is an uncertainty in time and Δf is an uncertainty in frequency. Consequently, loudspeaker-room acoustic equalization may be difficult to achieve with FIR filters at low frequencies.
What is neither disclosed nor suggested in the art is a loudspeaker system that overcomes the problems and limitations described above. More particularly, what is neither disclosed nor suggested is a loudspeaker system employing an FIR filter that performs well at low frequency.
The invention may be directed to dealing with low frequency limitation issues of FIR filters as applied to loudspeaker digital signal processing (DSP). More particularly, the invention may be directed to correcting magnitude and phase of FIR filters at low frequencies via Heyser Spiral curve fitting in the FIR coefficient generation process. A three-dimensional curve fit may be performed based on the desired magnitude and phase of a target transfer function. For low enough order polynomials, the fit can be used to obtain a low frequency response that approximately hits the average target magnitude and phase response below the low frequency limit of the FIR filter.
The invention comprises, in one form thereof, a method of operating a loudspeaker including providing a digital audio signal and identifying a target transfer function to be applied to the signal. At least one coefficient of an FIR filter is generated. The generating includes performing Heyser spiral curve fitting, and fitting a three-dimensional curve based on a magnitude and phase of a target transfer function. The digital audio signal is filtered through the FIR filter. The filtered signal is inputted into the loudspeaker.
The invention comprises, in another form thereof, a method of operating a loudspeaker, including providing a digital audio signal. A frequency is selected below which an FIR filter is to be corrected. Magnitude and phase of the filter frequency response are fitted by separate low-order polynomial functions below this frequency and converge to a calculated transfer function above this frequency. The digital audio signal is filtered through the FIR filter. The filtered signal is inputted into the loudspeaker.
The invention comprises, in yet another form thereof, a loudspeaker arrangement including a loudspeaker having an input, and a digital FIR filter having an input and an output. The input of the filter receives an audio signal. The output is coupled to the input of the loudspeaker. Coefficients of the filter are created using the Heyser spiral correction method to correct or improve low frequency response of the filter. The frequency response of the FIR filter is defined by a multi-dimensional polynomial at low frequencies and is calculated by conjugation to a target at high frequencies.
The above mentioned and other features and objects of this invention, and the manner of attaining them, will become more apparent and the invention itself will be better understood by reference to the following description of embodiments of the invention taken in conjunction with the accompanying drawings, wherein:
Corresponding reference characters indicate corresponding parts throughout the several views. Although the exemplification set out herein illustrates embodiments of the invention, in several forms, the embodiments disclosed below are not intended to be exhaustive or to be construed as limiting the scope of the invention to the precise forms disclosed.
Referring now to the drawings, and particularly to
A primary metric in determining the performance of a loudspeaker is its frequency response F(ω). This frequency response is a complex function that contains both magnitude and phase data, but the response is typically looked at only in terms of magnitude on a logarithmic scale (dB). One alternate method of looking at frequency response data is a three-dimensional visualization known as a Heyser Spiral. This visualization method plots the real component of the frequency response on the x-axis, the imaginary component of the frequency response on the y-axis, and frequency on the z-axis. A Heyser Spiral Correction method of the present invention for generating FIR filters may exploit this Heyser Spiral visualization method for applying low frequency correction to FIR filters.
In
One typical method of generating FIR filter coefficients for a loudspeaker response is to simply calculate the complex conjugate of the loudspeaker's frequency response function, H(ω).
Then, taking the inverse Fast Fourier Transform (FFT) of H(ω), truncating this function and applying a Hamming window yields an FIR filter coefficient set of length L, as shown by Equation (2):
where n denotes the sample number and w[n] is the hamming window function
This method produces errors in the magnitude and phase response of the FIR filter at low frequencies because of the time-frequency uncertainty principle. FIR filters calculated from a conjugation of frequency response of a loudspeaker with respect to some target transfer function may deviate from the desired response at low frequencies. Illustrating this,
An example plot of a group delay through a filter calculated from a direct conjugation of a loudspeaker's frequency response is shown in
Because an FIR filter is, by definition, of finite length, the frequency resolution of such a filter is restricted. Frequency resolution limitations cause errors in the FIR filter coefficients when calculated as described above. These errors manifest themselves as deviations from the target frequency and phase response. The error of the filter may be seen in its Heyser Spiral, where a magnitude/phase error made be apparent as a loop at low frequency. Frequency and phase response errors in the filter manifest themselves as small “loops” in the Heyser spiral, as shown in
A qualitative understanding of the Heyser spiral correction method of the invention may be gained from an analogy to Gibbs phenomenon, which is illustrated in
The Heyser Spiral Correction method of the invention may repair the Heyser Spiral of the filter by fitting low order polynomials to the frequency responses and/or phase responses of the target filter at midrange frequencies. The method may work particularly well with a low frequency magnitude specified by the user. The low order polynomial fit may generate transitions in the Heyser Spiral that are more gradual, as illustrated in
A Heyser spiral correction may be implemented by selecting a low frequency limit, ωL, based on the desired length of the FIR filter, L. A new target curve may then be constructed such that for ω≦ωL, H(ω) becomes HL(ω) where HL(ω) is a polynomial of low order in logarithmic magnitude space (dB) and of low order in unwrapped phase space. This may produce a corrected FIR filter coefficient set that is well behaved in both magnitude and phase at low frequencies, as shown in
The application of the method of the invention is not limited to acoustics or loudspeaker DSP. Rather, the method may be applied more generally to a generic device with a frequency response F(ω). The desired frequency response of the device may not be unity for all frequencies, as indicated by equation (1) above. Thus, the desired frequency response of the device may be generalized as an arbitrary function, A(ω). Hence, equation (1) becomes
A frequency ωL may then be selected based on the length of the FIR filter and the behavior of H(ω). The application of a polynomial fitting function for a) ω≦ωL may call for H(ω) to be sufficiently smooth in the vicinity of ωL so that the polynomial low frequency function mates well with H(ω). That is, the combination of the polynomial low frequency function and H(ω) may be a continuous function in the vicinity of ωL. Once ωL is selected, the low order polynomial correction may be applied in magnitude space and phase space, so H(ω) becomes
where cn and bk are the respective polynomial coefficients for the logarithmic magnitude and unwrapped phase functions. From
The parameters ωL, the fit coefficients, as well as the polynomial fitting orders, N and K can be placed into an optimization function which minimizes the error of the frequency response of FIRHS with respect to the target frequency response, H(ω).
The present invention has been described herein as applying to a FIR filter for loudspeaker DSP. However, it is to be understood that the method of the invention applies to the creation of any FIR filter that is created with the intention of doing frequency response correction at low frequencies.
In
In a next step 1004, a target transfer function to be applied to the signal is identified. Preparation for determining a desired loudspeaker transfer function may include acquiring information regarding both local acoustic properties at the listening position within a three-dimensional sound field space and the acoustic power in the three-dimensional sound field. The target transfer function may be identified based upon this acquired information by use of techniques known in the art.
Next, in step 1006, at least one coefficient of an FIR filter is generated. The generating includes performing Heyser spiral curve fitting, and fitting a three-dimensional curve based on a magnitude and phase of the target transfer function. The Heyser spiral curve fitting may generally include repairing the “small loop” artifact of a Heyser spiral (e.g., see
In step 1008, the digital audio signal is filtered through the FIR filter. For example, as shown in
In a final step 1010, the filtered signal is inputted into the loudspeaker. For example, as also shown in
Another embodiment of a method 1100 of the present invention for operating a loudspeaker is illustrated in
In a next step 1104, a frequency below which an FIR filter is to be corrected is selected. That is, a cutoff frequency at which there is a substantial difference between a target transfer function value and an actual transfer function value for a loudspeaker FIR filter may be determined. For example, a highest frequency at which the difference between the target transfer function value and the actual transfer function value exceeds a threshold difference may be determined. More generally, a frequency may be ascertained at an upper end of a range of frequencies in which the difference between the target transfer function value and the actual transfer function value for the FIR filter exceeds the threshold value.
As shown in the example plot of
The frequency 100 Hz may be chosen somewhat arbitrarily as the approximate frequency in
In step 1106, magnitude and phase of the filter's frequency response are fitted by separate low-order polynomial functions below the selected frequency. The magnitude and phase converge to a calculated transfer function above the selected frequency. In a specific example, for frequencies ω below the low frequency limit ωL, i.e., for ω≦ωL, the magnitude and phase of a frequency response H(ω) of filter 12 are fitted by separate low-order polynomial functions below the selected frequency. For these frequencies ω below the low frequency limit ωL, the magnitude and phase of a frequency response H(ω) of filter 12 may be defined by a polynomial of low order in logarithmic magnitude space (dB) and of low order in unwrapped phase space.
In step 1108, the digital audio signal is filtered through the FIR filter. For example, as shown in
In a final step 1110, the filtered signal is input into the loudspeaker. For example, as also shown in
While this invention has been described as having an exemplary design, the present invention may be further modified within the spirit and scope of this disclosure. This application is therefore intended to cover any variations, uses, or adaptations of the invention using its general principles.