Time delay and integration

Fig. 6.1a c. Different approaches to image scanning with an array of detectors, (a) Parallel scan with a linear array, (b) Serial scan with a linear array using time delay and integration (TDl). (c) Se-ries/parallel scan with a two-dimensional array using TDl... 

Series/Parallel Scan with time delay and integration remains the principal approach to advanced thermal imaging systems. However, for applications where only a small number of resolution elements are needed, two-dimensional staring detector arrays with CCD or CID readout are being considered [8.106]. This does away with the scanner and a focal optics used with conventional systems. However, to compensate for nonuniformities, both dc offset and gain correction must be made on a pixel by pixel basis. Detector responsivity and readout nonlinearities will increase the number of computations needed for sufficient correction and only experience with the stability of different types of arrays will determine how often the correction algorithms must be calibrated [8.107,108]. 

Control of integrating processes with time delay and inverse response (IPTD8t.IV)... 

Fig. 22. Time-resolved emission of Pt(2-thpy)2 dissolved in n-octane (c = 10 mol/1) and monitored at T = 1.3 K. Excitation Xxc = 337.1 nm, pulse width = 0.5 ns, repetition rate 100 Hz. (a) The emission is detected without any delay and integrated over Af = 500 ns. (b) Detection of the emission after a delay of f = 10 ps and integrated over At = 60 ps. The energies of the vibrational satellites are given in cm relative to the electronic origin II (a) and origin I (b), respectively. (Compare Ref. [60])...

Y = KKc for proportional mode, tIt, for integral mode, and tqIt for derivative mode. 9, r are the time delay and time constant based on the process reaction curve, respectively. 

In Chapter 5 we discussed the dynamics of relatively simple processes, those that can be modeled as either first- or second-order transfer functions or as an integrator. Now we consider more complex transfer function models that include additional time constants in the denominator and/or functions of s in the numerator. We show that the forms of the numerator and denominator of the transfer function model influence the dynamic behavior of the process. We also introduce a very important concept, the time delay, and consider the approximation of comphcated transfer function models by simpler, low-order models. Additional topics in this chapter include interacting processes, state-space models, and processes with multiple inputs and outputs. 

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