Analog And Digital Signal Processing:2nd (Second) Edition [NEW] Download
CLICK HERE >>> https://shurll.com/2sZazm
The DSP design is derived from that on the THEMIS spacecraft (Cully et al. 2007) with modifications that enhance the frequency response, for example, the sample rates are significantly higher. This unit receives nine signals (six voltage signals from the SDP and ADP and three signals from the SCM). It creates the electric field signals in analog, performs analog signal conditioning, the analog to digital conversion, and digital signal processing on the scientific signals. The digital signal processing includes digital filtering, spectral processing, burst memory, solitary wave detection, and data compression inside of a field-programmable gate array (FPGA). It also creates calibration signals for the SCM.
The DSP (Fig. 4) receives nine analog signals from the ADP, SDP, and SCM sensors. It performs analog signal conditioning, A/D conversion, and digital signal processing using a FPGA (Actel Corporation RTAX2000). The DSP also creates calibration signals for the SCM.
There are two DSPs on each of the MMS spacecraft. One is active while the other is an unpowered spare. The units are identical except for the signal connections and minor grounding differences. DSP A receives the analog signals and routes them directly to DSP B. The analog inputs are high impedance on each of the DSP units, so the powered-off unit does not disturb the sensor signals. The BEB, AEB, and SCM grounds are connected through DSP A directly while both DSP A and DSP B are connected to analog ground on a common backplane. There are no significant differences in performance between the two units. More information on the redundant operation of the FIELDS suit is in Torbert et al. (2014, this issue).
The network model was fit to the ADP calibrations. In performing the fit, C sh , C in , f cbl , f 1, f 2, and τ D are varied (under limits) to obtain the best result. The red lines in Fig. 6 shows the best fit to the preamplifier response in gain (top panel) and phase (bottom panel). These fits indicate that the network model, while simplified, represents the preamplifier response well. Developing such a model is critical since it allows for digital correction to the measured electric field signal. Without such correction, for example, a bipolar electron phase-space hole may appear to be a tri-polar structure due to the distortion of the complex transfer function of the preamplifier and AEB system.
The DSP flexibility, while scientifically valuable, creates a great challenge in digital testing and calibration. Each of the science signals has a number of configurations and data rates. For example, E12 (DC-coupled) can be set to any of 16 data rates. The spectral averaging can be adjusted and the broadband filters can have adjustable output rates and/or can be set to peak, average, or both. Including all signals (and analog-generated signals), the DSP basically has 2N configurations, where N is on the order of 1000, making the DSP impossible to fully test. Since digital processing is identical on all of signals, the effort concentrated on (1) calibration of individual channels at their native rates, (2) calibration of the planned in-flight configurations, and (3) automated verification of each of the signals at all of their configurations while the other signals remain in a nominal configuration.
A signal is an electromagnetic or electrical current that carries data from one system or network to another. In electronics, a signal is often a time-varying voltage that is also an electromagnetic wave carrying information, though it can take on other forms, such as current. There are two main types of signals used in electronics: analog and digital signals. This article discusses the corresponding characteristics, uses, advantages and disadvantages, and typical applications of analog vs. digital signals.
A digital signal is a signal that represents data as a sequence of discrete values. A digital signal can only take on one value from a finite set of possible values at a given time. With digital signals, the physical quantity representing the information can be many things:
Digital signals are used in all digital electronics, including computing equipment and data transmission devices. When plotted on a voltage vs. time graph, digital signals are one of two values, and are usually between 0V and VCC (usually 1.8V, 3.3V, or 5V) (see Figure 2).
Analog circuits can be complex designs with multiple components, or they can be simple, such as two resistors that form a voltage divider. In general, analog circuits are more difficult to design than digital circuits that accomplish the same task. It would take a designer who is familiar with analog circuits to design an analog radio receiver, or an analog battery charger, since digital components have been adopted to simplify those designs.
Analog signals are commonly used in communication systems that convey voice, data, image, signal, or video information using a continuous signal. There are two basic kinds of analog transmission, which are both based on how they adapt data to combine an input signal with a carrier signal. The two techniques are amplitude modulation and frequency modulation. Amplitude modulation (AM) adjusts the amplitude of the carrier signal. Frequency modulation (FM) adjusts the frequency of the carrier signal. Analog transmission may be achieved via many methods:
Much like the human body uses eyes and ears to capture sensory information, analog circuits use these methodologies to interface with the real world, and to accurately capture and process these signals in electronics.
Unlike analog circuits, most useful digital circuits are synchronous, meaning there is a reference clock to coordinate the operation of the circuit blocks, so they operate in a predictable manner. Analog electronics operate asynchronously, meaning they process the signal as it arrives at the input.
Most digital circuits use a digital processor to manipulate the data. This can be in the form of a simple microcontroller (MCU) or a more complex digital signal processor (DSP), which can filter and manipulate large streams of data such as video.
Digital signals are commonly used in communication systems where digital transmission can transfer data over point-to-point or point-to-multipoint transmission channels, such as copper wires, optical fibers, wireless communication media, storage media, or computer buses. The transferrable data is represented as an electromagnetic signal, such as a microwave, radio wave, electrical voltage, or infrared signal.
Many systems must process both analog and digital signals. It is common in many communications systems to use an analog signal, which acts as an interface for the transmission medium to transmit and receive information. These analog signals are converted to digital signals, which filter, process, and store the information.
Figure 5 shows a common architecture in which the RF analog front-end (AFE) consists of all analog blocks to amplify, filter, and gain the analog signal. Meanwhile, the digital signal processor (DSP) section filters and processes the information. To convert signals from the analog subsystem to the digital subsystem in the receive path (RX), an analog-to-digital converter (ADC) is used. To convert signals from the digital subsystem to the analog subsystem in the transmit path (TX), a digital-to-analog converter (DAC) is used.
A digital signal processor (DSP) is a specialized microprocessor chip that performs digital signal processing operations. DSPs are fabricated on MOSFET integrated circuit chips, and are widely used in audio signal processing, telecommunications, digital image processing, high-definition television products, common consumer electronic devices such as mobile phones, and in many other significant applications.
A DSP is used to measure, filter, or compress continuous real-world analog signals. Dedicated DSPs often have higher power efficiency, making them suitable in portable devices due to their power consumption constraints. A majority of general-purpose microprocessors are also able to execute digital signal processing algorithms.
A DAC provides the reverse operation. The DAC input is a binary stream of data from the digital subsystem, and it outputs a discrete value, which is approximated as an analog signal. As the resolution of the DAC increases, the output signal more closely approximates a true smooth and continuous analog signal (see Figure 7). There is usually a post filter in the analog signal chain to further smooth out the waveform.
As with most engineering topics, there are pros and cons for both analog and digital signals. The specific application, performance requirements, transmission medium, and operating environment can determine whether analog or digital signaling (or a combination) should be used.
Although many original communication systems used analog signaling (telephones), recent technologies use digital signals because of their advantages with noise immunity, encryption, bandwidth efficiency, and the ability to use repeaters for long-distance transmission. A few digital signal applications are listed below:
The goal of a DSP is usually to measure, filter or compress continuous real-world analog signals. Most general-purpose microprocessors can also execute digital signal processing algorithms successfully, but may not be able to keep up with such processing continuously in real-time. Also, dedicated DSPs usually have better power efficiency, thus they are more suitable in portable devices such as mobile phones because of power consumption constraints. DSPs often use special memory architectures that are able to fetch multiple data or instructions at the same time.
Digital signal processing (DSP) algorithms typically require a large number of mathematical operations to be performed quickly and repeatedly on a series of data samples. Signals (perhaps from audio or video sensors) are constantly converted from analog to digital, manipulated digitally, and then converted back to analog form. Many DSP applications have constraints on latency; that is, for the system to work, the DSP operation must be completed within some fixed time, and deferred (or batch) processing is not viable. 2b1af7f3a8