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range (fast time) for a single transmitted pulse. It crosses the threshold at three

               different times, suggesting the presence of three targets at different ranges.




























               FIGURE 1.24   Illustration of threshold detection.



                     Because  they  are  the  result  of  a  statistical  process,  threshold  detection
               decisions have a finite probability of being wrong. For example, a noise spike
               could cross the threshold, leading to a false target declaration, commonly called
               a false alarm. These errors are minimized if the target spikes stand out strongly
               from the background interference, i.e., if the SIR is as large as possible. If this is
               the case the threshold can be set relatively high, resulting in few false alarms
               while still detecting most targets. This fact also accounts for the importance of
               matched filtering in radar systems. The matched filter maximizes the SIR, thus

               providing the best threshold detection performance. Furthermore, the achievable
               SIR  increases  monotonically  with  the  transmitted  pulse  energy E,  thus
               encouraging  the  use  of  longer  pulses  to  get  more  energy  on  the  target.  Since
               longer  simple  pulses  reduce  range  resolution,  the  technique  of  pulse
               compression  is  also  important  so  that  fine  resolution  can  be  obtained  while

               maintaining good detection performance.
                     The concept of threshold detection can be applied to many different radar
               signal processing systems. Figure 1.24 illustrates its application to a fast-time
               (range) signal trace, but it can be equally well applied to a signal composed of
               measurements at different Doppler frequencies for a fixed range, or in a two-
               dimensional form to combined range-Doppler data or to SAR imagery.
                     There are numerous significant details in implementing threshold detection.

               Various  detector  designs  work  on  the  magnitude,  squared-magnitude,  or  even
               log-magnitude of the complex signal samples. The threshold is computed from
               knowledge  of  the  interference  statistics  so  as  to  limit  false  alarms  to  an
               acceptable rate. However, in real systems the interference statistics are rarely
               known accurately enough to allow for precomputing a fixed threshold. Instead,
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