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content/doa.rst
@@ -416,8 +416,7 @@ We can implement the equations above in Python fairly easily:
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Rinv = np.linalg.pinv(R) # 3x3. pseudo-inverse tends to work better than a true inverse
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w = 1/(a.conj().T @ Rinv @ a) # MVDR equation! denominator is 1x3 * 3x3 * 3x1
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- metric = metric[0,0] # convert the 1x1 matrix to a Python scalar, it's still complex though
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- metric = np.abs(metric) # take magnitude
+ metric = np.abs(w[0,0]) # take magnitude
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metric = 10*np.log10(metric) # convert to dB so its easier to see small and large lobes at the same time
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results.append(metric)
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