Principles of Modern Radar - Volume 2 1891121537

17.3 Direct Signal and Multipath/Clutter Cancellation Techniques 755signal, the SNR loss for a target at range bin l and Doppler bin, m can be written as{1 sin [ πm (n C − l) / N ] }L[l,m] =−20 log 10n C sin ( πm / N ) (17.11)For l = 0, the same loss of the batches algorithm given in equation (17.9) is obtainedat the m-th Doppler bin, but the SNR loss for a given n C increases at higher range bins.Thus, the integration loss is maximized at the highest Doppler and range values consideredin the 2D-CCF.As an example, Figure 17-5b shows maximum SNR loss and computational load(number of complex multiplications) as a function of the number n C of channels forthe study case described in Table 17-2. For any number of channels within the allowedrange, the channelization technique yields a computational load reduction of two ordersof magnitude with respect to the optimum techniques but might yield an SNR loss of 6 dBif n C is the minimum allowable value. Table 17-2 reports the results of the channelizationtechnique operating with n C = 500, which limits the SNR loss to 4 dB in the worstlocation within the 2D-CCF but requires the smallest number of complex operations.SNR loss evaluation gives only limited insight into the surveillance capability of theresulting PBR system. However, the sources of opportunity usually provide CW waveforms,and, for the real-time operation, only a fraction of the available signals is typicallyused for signal detection due to the limited computational resources available. Under theseconditions a suboptimum algorithm for evaluating the 2D-CCF potentially increases theradar updating rate while operating with the same computational resources, thus significantlyimproving the track initiation stage. Alternatively, computational resources savedby the suboptimum algorithm might be exploited to process data coming from parallelchannels (e.g., multiple antennas, multiple frequency channels); integrating the obtainedresults allows recovery of the SNR loss and, potentially, improvement of the target detectionperformance by exploiting the diversity of information conveyed by the multiplechannels, as described in Section 17.6.The channelization technique gives the option of using only a subset of the originaldata for computing the final result, such as by discarding some of the frequency channels[27]. This is quite reasonable for many signals of opportunity in which most of the powerlies in only a fraction of the sampled bandwidth. This approach would yield additional SNRloss and a degraded range resolution but provides a preliminary estimate of the 2D-CCFby processing a limited amount of data, which might be of great interest when there aretight constraints on the data transfer capability (e.g., in distributed systems). Moreover,channelization based on the DFT is only one such method. Alternative channelizationmethods might be developed based, for example, on the Walsh transform. Filters based onWalsh transform show higher sidelobes but are computationally cheaper since they requiremultiplications by ±1 coefficients.17.3 DIRECT SIGNAL AND MULTIPATH/CLUTTERCANCELLATION TECHNIQUESAs is intrinsic in the passive radar concept that involves parasitically exploiting an existingtransmitter of opportunity, the characteristics of the transmitted waveform are not under thecontrol of the radar designer and are not tailored for radar application. Because they are used