Merge pull request cupy#8077 from asi1024/mvdr

Add `cupyx.signal.mvdr`

cupyx/signal/__init__.py

@@ -10,3 +10,4 @@
 from cupyx.signal._radartools import pulse_doppler  # NOQA
 from cupyx.signal._radartools import cfar_alpha  # NOQA
 from cupyx.signal._radartools import ca_cfar  # NOQA
+from cupyx.signal._radartools import mvdr  # NOQA

cupyx/signal/_radartools/__init__.py

@@ -1,3 +1,4 @@
+from cupyx.signal._radartools._beamformers import mvdr  # NOQA
 from cupyx.signal._radartools._radartools import pulse_compression  # NOQA
 from cupyx.signal._radartools._radartools import pulse_doppler  # NOQA
 from cupyx.signal._radartools._radartools import cfar_alpha  # NOQA

cupyx/signal/_radartools/_beamformers.py

@@ -0,0 +1,60 @@
+# Copyright (c) 2019-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a
+# copy of this software and associated documentation files (the "Software"),
+# to deal in the Software without restriction, including without limitation
+# the rights to use, copy, modify, merge, publish, distribute, sublicense,
+# and/or sell copies of the Software, and to permit persons to whom the
+# Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+# DEALINGS IN THE SOFTWARE.
+
+import cupy as cp
+
+
+def mvdr(x, sv, calc_cov=True):
+    """
+    Minimum variance distortionless response (MVDR) beamformer weights
+
+    Parameters
+    ----------
+    x : ndarray
+        Received signal or input covariance matrix, assume 2D array with
+        size [num_sensors, num_samples]
+
+    sv: ndarray
+        Steering vector, assume 1D array with size [num_sensors, 1]
+
+    calc_cov : bool
+        Determine whether to calculate covariance matrix. Simply put, calc_cov
+        defines whether x input is made of sensor/observation data or is
+        a precalculated covariance matrix
+
+    Note: Unlike MATLAB where input matrix x is of size MxN where N represents
+    the number of array elements, we assume row-major formatted data where each
+    row is assumed to be complex-valued data from a given sensor (i.e. NxM)
+    """
+    if x.shape[0] > x.shape[1]:
+        raise ValueError(
+            "Matrix has more sensors than samples. Consider \
+            transposing and remember cuSignal is row-major, unlike MATLAB"
+        )
+
+    if x.shape[0] != sv.shape[0]:
+        raise ValueError("Steering Vector and input data do not align")
+
+    if calc_cov:
+        x = cp.cov(x, dtype=x.dtype)
+
+    wB = cp.linalg.inv(x).dot(sv)
+    wA = sv.conj().dot(wB)  # 1x1 scalar
+    return wB / wA

tests/cupyx_tests/signal_tests/radartools_tests/test_radartools.py

@@ -148,3 +148,12 @@ def test_ca_cfar2d(xp, dtype, shape, gc, rc):
 def test_ca_cfar2d_failures(shape, gc, rc):
     with pytest.raises(ValueError):
         _, _ = signal.ca_cfar(cupy.zeros(shape), gc, rc)
+
+
+@testing.for_float_dtypes(no_float16=True)
+def test_mvdr(dtype):
+    x = cupy.array([[1, 2, 3], [4, 5, 7]], dtype=dtype)
+    sv = cupy.array([1, 2], dtype=dtype)
+    out = signal.mvdr(x, sv)
+    assert out.dtype == dtype
+    testing.assert_allclose(out, [-2, 1.5])