【正文】
the second step is to calculate the estimation error by paring the filter output with a desired output. During the adaptive process the tap weights of the filter will be adjusted in accordance with the estimation error, so a new set of taps will be determined. Those two steps work together, and constitute a feedback loop, the result of which is to make the estimation error approach zero. When there exists noise, after repeating the two processes several times, the output estimation error of LMS filter will be converged to the acceptable level. Thus the three relations can be given as below: ① Filter output: . ( ) ( ) ( )Ty n d n x n? . (4) ② Estimation error: . ( ) ( ) ( )e n r n y n??. (5) ③ Tapweight adjustment: ( 1 ) ( ) ( ) ( )d n d n x n e n?? ? ?, (6) whered(n)denotes the tap of the filter,x(n) denotes the input vector of filter,μis called the step factor, which determines the convergence speed of the LMS filter. In the next step, we propose the way to apply the LMS adaptive filter to the direct wave cancellation. Based on the knowledge of LMS filter in the previous section, the key task is how to load the right LMS filter parameter from the model of direct wave. Figure 1 is the block diagram of the adaptive direct wave cancellation with the input reference wave and echo wave, whose output is the with the standard relations of LMS adaptive relations, the input vector x(n) is posed of some delays of the reference wave, and the taps of the filter d(n) correspond to the factors na in Eq.(3). When the adaptive arithmetic reaches the convergence point, the estimation error of the filter is the echo wave signal whose direct wave is largely removed. In a practical radar system, when there is no interested object in the detected space, a set of tapweights can be got by using the LMS adaptive filter, so the model of the direct wave is established, and the tapweights are stored in the memory of the DSP system. When the passive radar system works, the stored tapweights are recalled to fulfil the direct wave cancellation. The cancellation operation can be expressed by: ( ) ( ) ( ) ( )Tf n r n d n x n?? (7) wherer(n)denotes the echo wave signal,x(n)denotes the input vector, that consists of the delays of reference wave, andd(n)denotes the tapweight of the LMS adaptive filter. 3 Some Simulative Result To evaluate the performance of LMS adaptive direct wave cancellation, some simulations should be done before putting it into practical applications. Under the Matlab environment, which includes some subroutings such as the FM broadcast signal generator, the channel noise adder, the direct wave forming and the LMS adaptive filter program, the simulation routings are developed. In the FM broadcast signal generator subrouting, first the FM parameters are initialized according to th