Abstract: This article introduces a digital anti-noise module based on a dedicated DSP chip and a unique software anti-noise algorithm, which achieves a voice clarity not less than 98 in a 120 decibel noise environment. This module has been successfully used in my country's airborne communication equipment.
Overview The current third-generation anti-noise products in China use dynamic noise reduction (DNR) technology. DNR technology dynamically adjusts the output voice switch by changing the voice peak value, so as to achieve the purpose of noise reduction. Although it is currently a better anti-noise analog processing technology, it also has some limitations, including light note drop characters and strong tone noise tailing; the noise reduction effect is focused on low frequencies; the noise reduction is completely realized by hardware circuits. Problems such as troublesome debugging and maintenance. Due to these problems, the mass promotion and application of analog DNR noise reduction products are restricted. With the rapid development of digital signal processing technology, digital anti-noise technology products supported by digital signal processors and related algorithms continue to emerge. The digital anti-noise module proposed in this paper is the application of modern digital signal processing (DSP) technology and the characteristics of high-speed real-time processing operations, using corresponding software algorithms to process voice and noise in a high-noise environment, and complete the high-noise environment Voice communication function.
The performance advantages of this module include:
a) The software uses an adaptive filtering algorithm. The digital anti-noise processor can generally suppress noise above 50 decibels, and the output voice is stable, without missing words and noise tailing.
b) The digital anti-noise processor equalizes the noise reduction in the entire voice band (300~3000Hz).
c) The digital anti-noise processor can meet different anti-noise requirements by changing the software algorithm, facilitating product upgrades.
d) The hardware cost is lower than that of analog DNR products.
e) Using software encryption technology, the product is not easy to be infringed or counterfeited, which is beneficial to protect the interests of manufacturers.
Main index requirements and overall solution ideas This digital anti-noise processing module is a part of JK-DP10 digital anti-noise processor, mainly used for communication in noisy environments such as airborne communication terminal equipment, and its transmission frequency range is 300~3400Hz , The flatness is not more than 2dB. The noise reduction performance is: when a 3mV, 2-second intermittent sine wave signal is added to the input of the module (the frequency is 300Hz, 700Hz, 1000Hz, 1500Hz, 2000Hz, 2500Hz, 3000Hz) and a 3mV, 120dB continuous white noise signal is added, the module The difference in output level is not less than 50dB.
First, choose a suitable DSP device. It is required to have low power consumption, high-speed data operation and throughput capability (above 40 MIPS), including A/D, D/A, and Flash flash memory (16KB). Then establish an effective noise model, design an adaptive filtering structure and related software algorithms. Next, the electromagnetic compatibility (EMC) of the digital anti-noise processor is designed, and an anti-noise microphone device that can adapt to 120dB environmental noise is selected. The combination of DSP hardware and related software algorithms enables the digital anti-noise processor to achieve a voice clarity of not less than 98 in a 120dB high-noise environment.
figure 1
Software and hardware design scheme Main working principle This processor mainly completes the high-definition communication function of voice in high-noise environment. The voice signal and environmental noise are input to the pre-amplification stage through the MIC. The function of the pre-amplification stage is to amplify the voice and environmental noise to the amplitude that can be recognized by the A/D in the dedicated DSP chip, so that the A/D can convert the signal normally. After A/D conversion, the analog signal becomes a 12-bit digital signal and enters the arithmetic unit of the DSP. The DSP completes the measurement of the ambient noise within the first 3 seconds and establishes a mathematical model, and then processes the voice and noise according to the given algorithm , The processing result is sent to D/A through the data bus, and then sent to the post-amplifier after smoothing and filtering. The function of the post-amplifier is to meet the input requirements of related equipment.
DSP chip selection The JK-DP10 digital anti-noise processor designed in this article has higher requirements for the digital signal processor chip. The chip must not only have strong real-time processing performance, but also high computing speed and data throughput; it also requires low power consumption. The external A/D, D/A and Flash flash memory are best integrated in the DSP. Reduce product volume. Therefore, one of the TMS320C5XX series DSP chips is selected as the processing chip, with high-speed A/D, D/A and 32KB Flash for program loading.
Software algorithm scheme The digital anti-noise processor is implemented by an adaptive filter. The adaptive filter has the ability to track changes in the signal and noise, so that the characteristics of the filter also change with the changes in the signal and noise to achieve the optimal filtering effect.
The characteristic change of the adaptive filter is realized by the adaptive algorithm by adjusting the filter weight coefficients. In general, an adaptive filter consists of two parts, one is the filter structure, and the other is an adaptive algorithm for adjusting filter coefficients. The structure of the adaptive filter adopts the FIR structure. For the processing of in-band white noise, the classic LMS algorithm cannot achieve the optimal noise reduction effect. It is necessary to use the autocorrelation characteristics and power spectral density characteristics of the noise, and make appropriate adjustments on the basis of the LMS algorithm to achieve the best Noise reduction effect.
The DSP implementation structure of the digital anti-noise microphone group is shown in Figure 1.
The original input signal d(n) includes signal and noise, and x(n) is the reference noise input. This adaptive filter essentially completes the noise estimation in d(n), and subtracts the estimated value y(n) from the original channel to achieve the result of noise elimination. Of course, the estimated value y(n) is compared with the original input The signal is not a simple algebraic subtraction, but a set of corresponding software algorithms, such as power spectrum analysis of related power.
In Figure 1, the adaptive filter adopts a transverse structure, and the output y(n) of the filter is expressed as:
N- 1
y(n) = ∑ Wi (n- i)
i =0
N is the order of the filter.
Software design The complexity of an adaptive filter implementation is usually measured by the number of multiplications and order it needs. For the adaptive filter system based on DSP, the data throughput and data processing speed of the DSP chip are also very important. This digital anti-noise processor uses a 120-order adaptive digital filter, and selects a DSP chip with a calculation speed of 40MIPS as the main processor. Because the DSP chip contains A/D and D/A and 16KB of flash memory, these On-chip resources make the implementation of adaptive filters more effective.
According to the autocorrelation characteristics and power density of the noise, the software not only uses the LMS algorithm in the traditional symmetrical transverse structure FIR filter, but also estimates the power spectral density of the noise and signal, that is, the 16 values ​​of the sample code Perform square accumulation to find the average power value, compare it with the power value of the previous point, and divide the compared difference with the set noise threshold. If the result is greater than 1, then adjust the weight of the filter to change Smaller, the signal output amplitude becomes larger, if the result is less than or equal to 1, the weight coefficient of the filter becomes larger, and the signal output amplitude becomes smaller.
Custom-made special anti-noise DSP chip After the debugging work is completed, it is handed over to a company specializing in making DSP chips to make a special DSP chip with anti-noise function. After actual measurement, the power consumption of the whole machine is not more than 70mA, and the lead-out pins of the DSP chip are reduced to 64 pins, which greatly reduces the area of ​​the printed circuit board. Because the software code is masked in the chip at a time, the trouble of writing the code every time is eliminated, and the workload of debugging is reduced. Under normal circumstances, the module can be completed with only 3 points of debugging, which greatly reduces the cost of debugging and is conducive to mass production.
Conclusion The digital anti-noise module uses DSP chips and adaptive technology, which not only improves the anti-noise performance of communication products, but also reduces production costs. This module has been successfully applied to my country's airborne communication equipment.
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