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diff --git a/src/main/java/org/apache/commons/math3/filter/DefaultProcessModel.java b/src/main/java/org/apache/commons/math3/filter/DefaultProcessModel.java
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.commons.math3.filter;
+
+import org.apache.commons.math3.exception.DimensionMismatchException;
+import org.apache.commons.math3.exception.NoDataException;
+import org.apache.commons.math3.exception.NullArgumentException;
+import org.apache.commons.math3.linear.Array2DRowRealMatrix;
+import org.apache.commons.math3.linear.ArrayRealVector;
+import org.apache.commons.math3.linear.RealMatrix;
+import org.apache.commons.math3.linear.RealVector;
+
+/**
+ * Default implementation of a {@link ProcessModel} for the use with a {@link KalmanFilter}.
+ *
+ * @since 3.0
+ */
+public class DefaultProcessModel implements ProcessModel {
+    /**
+     * The state transition matrix, used to advance the internal state estimation each time-step.
+     */
+    private RealMatrix stateTransitionMatrix;
+
+    /** The control matrix, used to integrate a control input into the state estimation. */
+    private RealMatrix controlMatrix;
+
+    /** The process noise covariance matrix. */
+    private RealMatrix processNoiseCovMatrix;
+
+    /** The initial state estimation of the observed process. */
+    private RealVector initialStateEstimateVector;
+
+    /** The initial error covariance matrix of the observed process. */
+    private RealMatrix initialErrorCovMatrix;
+
+    /**
+     * Create a new {@link ProcessModel}, taking double arrays as input parameters.
+     *
+     * @param stateTransition the state transition matrix
+     * @param control the control matrix
+     * @param processNoise the process noise matrix
+     * @param initialStateEstimate the initial state estimate vector
+     * @param initialErrorCovariance the initial error covariance matrix
+     * @throws NullArgumentException if any of the input arrays is {@code null}
+     * @throws NoDataException if any row / column dimension of the input matrices is zero
+     * @throws DimensionMismatchException if any of the input matrices is non-rectangular
+     */
+    public DefaultProcessModel(
+            final double[][] stateTransition,
+            final double[][] control,
+            final double[][] processNoise,
+            final double[] initialStateEstimate,
+            final double[][] initialErrorCovariance)
+            throws NullArgumentException, NoDataException, DimensionMismatchException {
+
+        this(
+                new Array2DRowRealMatrix(stateTransition),
+                new Array2DRowRealMatrix(control),
+                new Array2DRowRealMatrix(processNoise),
+                new ArrayRealVector(initialStateEstimate),
+                new Array2DRowRealMatrix(initialErrorCovariance));
+    }
+
+    /**
+     * Create a new {@link ProcessModel}, taking double arrays as input parameters.
+     *
+     * <p>The initial state estimate and error covariance are omitted and will be initialized by the
+     * {@link KalmanFilter} to default values.
+     *
+     * @param stateTransition the state transition matrix
+     * @param control the control matrix
+     * @param processNoise the process noise matrix
+     * @throws NullArgumentException if any of the input arrays is {@code null}
+     * @throws NoDataException if any row / column dimension of the input matrices is zero
+     * @throws DimensionMismatchException if any of the input matrices is non-rectangular
+     */
+    public DefaultProcessModel(
+            final double[][] stateTransition,
+            final double[][] control,
+            final double[][] processNoise)
+            throws NullArgumentException, NoDataException, DimensionMismatchException {
+
+        this(
+                new Array2DRowRealMatrix(stateTransition),
+                new Array2DRowRealMatrix(control),
+                new Array2DRowRealMatrix(processNoise),
+                null,
+                null);
+    }
+
+    /**
+     * Create a new {@link ProcessModel}, taking double arrays as input parameters.
+     *
+     * @param stateTransition the state transition matrix
+     * @param control the control matrix
+     * @param processNoise the process noise matrix
+     * @param initialStateEstimate the initial state estimate vector
+     * @param initialErrorCovariance the initial error covariance matrix
+     */
+    public DefaultProcessModel(
+            final RealMatrix stateTransition,
+            final RealMatrix control,
+            final RealMatrix processNoise,
+            final RealVector initialStateEstimate,
+            final RealMatrix initialErrorCovariance) {
+        this.stateTransitionMatrix = stateTransition;
+        this.controlMatrix = control;
+        this.processNoiseCovMatrix = processNoise;
+        this.initialStateEstimateVector = initialStateEstimate;
+        this.initialErrorCovMatrix = initialErrorCovariance;
+    }
+
+    /** {@inheritDoc} */
+    public RealMatrix getStateTransitionMatrix() {
+        return stateTransitionMatrix;
+    }
+
+    /** {@inheritDoc} */
+    public RealMatrix getControlMatrix() {
+        return controlMatrix;
+    }
+
+    /** {@inheritDoc} */
+    public RealMatrix getProcessNoise() {
+        return processNoiseCovMatrix;
+    }
+
+    /** {@inheritDoc} */
+    public RealVector getInitialStateEstimate() {
+        return initialStateEstimateVector;
+    }
+
+    /** {@inheritDoc} */
+    public RealMatrix getInitialErrorCovariance() {
+        return initialErrorCovMatrix;
+    }
+}