创新对数电压-时间转换器提升模拟数字信号转换效率

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《对数电压-时间转换器在模拟信号数字化转换中的应用》是一本2019年出版的专业书籍，由Mauro Santos、Jorge Guilherme、Nuno Horta等多位作者合著，收录于LectureNotes in Electrical Engineering系列的第558卷。该书主要关注的是一个创新的对数转换架构，特别是一种基于交叉耦合放大器的对数电压-时间转换器（Logarithmic Voltage-to-Time Converter, LVT）。传统的对数模拟到数字转换器（Analog-to-Digital Converter, ADC）设计通常源于线性ADC架构，依赖于如放大器之类的模拟元件。然而，这本书所提出的转换器设计打破了常规，它提供了一种新型的、不依赖于线性转换原理的解决方案。在当前技术的背景下，大多数对数ADC都试图通过模拟电路实现非线性特性，以捕捉输入信号电压与量化误差之间的对数关系，从而提高在低电平信号处理中的精度。对数转换器的优势在于能够更好地适应信号的动态范围，减少量化噪声，并在一定程度上改善ADC的总体性能，特别是在音频、通信和信号处理等领域，对信号的动态范围变化敏感的应用中。本书详细介绍了该新型LVT的工作原理、设计方法和实现细节，可能包括对非线性电路的深入探讨、误差分析、以及针对实际应用的优化策略。此外，书中可能还包含了实验验证、仿真结果以及与其他传统ADC架构的比较，以展示其优越性和潜在的应用场景。作者团队涵盖了国际上多个知名大学和研究机构，如意大利那不勒斯大学、德国慕尼黑工业大学、中国浙江大学等，他们的专业背景涵盖了控制与机器人学、电子工程、信息技术等多个领域，确保了研究内容的深度和广度。《Logarithmic Voltage-to-Time Converter for Analog-to-Digital Signal Conversion》是一本具有前瞻性的技术著作，对于理解对数转换在模拟信号数字化处理中的重要性和未来发展具有重要的参考价值，为设计更高效、精度更高的ADC系统提供了新的思路和理论支持。

Fig. 6.10 Effect of ﬁxed offset and input polarity dependent offset

on the vo ltage-to-time transfer characteristic

................ 105

Fig. 6.11 Simpliﬁed model of bondpad, bonding wire, package and pin

parasitics

........................................... 106

Fig. 6.12 Transient simulation results with the chip to pin interconnect

model

............................................. 106

Fig. 6.13 Transient simulation result without inductance L

and

capacitance C

....................................... 107

Fig. 7.1 Calibration method block diagram

....................... 113

Fig. 7.2 Offset calibration scheme

.............................. 113

Fig. 7.3 Alternative offset calibration scheme

...................... 114

Fig. 7.4 Control voltage generation circuit

........................ 114

Fig. 7.5 Improved logarithmic conversion architecture

............... 115

xviii List of Figures

2 1 Introduction

Companding Nonlinear ADC architectures allow the representation of a high

dynamic range signal with less information or bits than otherwise required by a lin-

ear converter. However, to perform this function some information about the original

signal is lost in the conversion process. Companding can be useful or even a require-

ment in several areas, such as image acquisition or hearing aid apparatus. In the

case of image acquisition, companding can be useful in helping to cope with large

variations in brightness in a scene, such as zones of shadow and bright light [7]. In

the case of hearing aid apparatus, companding is a requirement. The reason is that it

is absolutely necessary to condition t he sound from the environment to conform to

the channel dynamic range allowable by the biological systems [10]. Other examples

of nonlinear converters used in medical applications, and where the converters have

been tailored speciﬁcally for that application, include advanced closed-loop neuro

stimulation applications [11, 12].

Other types of nonlinear converters perform a piecewise linear conversion, which

can be used to compensate nonlinearities in sensors, such as presented in [13–15].

These types of converters are also employed in nuclear physics [16]. Other types

of converters using pulse width modulation (PWM) can also compensate sensor

nonlinearities [17]. In this case, it is desirable that the complete system uses as little

power as possible to enable long operation times if running on battery power, or make

use of energy harvested from the environment. Thus, in order to minimize the energy

requirements, it is desirable that the analog-to-digital conversion is performed with

the lowest number of bits needed. In case a linear ADC architecture is used to convert

the analog output of nonlinear sensors, the conversion result will require additional

processing cycles to linearize, thus making the complete system require more power.

It might also require the usage of an ADC with a higher resolution than otherwise

needed to acquire the full signal range with the desired precision. This is the case

when, for any zone of interest, the sensor exhibits a small variation in the output

when the input stimulus varies widely.

Another type of nonlinear converters performs an ampliﬁcation of the input signal

before making the analog-to-digital conversion, as depicted in Fig. 1.1. This results

in a conversion characteristic that can be approximated by a straight line. Due to the

signal ampliﬁcation before quantization, small amplitude input signals will seem to

have been quantized with a higher resolution than higher amplitude signals. There

are examples of application of these types of converters in nuclear physics [18],

where the collision results can have very low and very high energies, and, also in

communication systems [19, 20], where the received signal amplitude varies widely

due to attenuation with distance or obstacles.

Some examples of nonlinear analog-to-digital converters found in the literature

and described in the f ollowing sections have been implemented with commercial of

the shelf (COTS) parts, however, only a small number of converters have been imple-

mented in recent technologies and operating at speeds comparable with the current

state-of-the-art for linear converters. In summary nonlinear conversion techniques

are clearly an open research area for many of today’s applications.

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