| Matched Filter |
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| CATEGORIES ABOUT MATCHED FILTER | |
| estimation theory | |
| telecommunication theory | |
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A matched filter is obtained by correlating with a time-reversed version of a signal (i.e. Convolution ) that we are looking for. Matched filters are commonly used in radar, in which a signal is sent out, and we measure the reflected signals, looking for something similar to what was sent out. Pulse Compression is an example of matched filtering. As a general rule of thumb, pulse width determines bandwidth of the filter we use. For example, if we send out a pulse having a pulse width of one microsecond, we'd generally use a filter having a bandwidth on the order of one megahertz, whereas a pulse of width one nanosecond would generally be picked up with a filter having a bandwidth on the order of one gigahertz. Shorter pulses spread the energy over wider bandwidth and thus need wider band filters that also admit more noise. Thus a longer pulse allows the filter to be more selective in frequency, but at the same time, is inherently less selective in time. This tradeoff establishes an Uncertainty Principle along the Canonical Conjugate Variables of time and frequency, or equivalently, along range and doppler. A plot that is a function of range and doppler is known as a Radar Ambiguity Function or radar ambiguity diagram. PROBLEM STATEMENT ''This section is only a stub. Please help improve it.'' The matched filter tries to maximize the output signal-to-noise ratio () between a filtered deterministic signal in stochastic additive noise. The observed sequence , is a linear combination of signal and noise . : : A filter h, is designed to maximize the SNR : EXAMPLE OF MATCHED FILTER As a specific example, suppose that we are looking for a signal with a frequency of one hertz. We correlate (compare) every incoming signal with a time-reversed signal of one hertz in order to detect or measure the target signal. |
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