diff --git a/gtsam_unstable/slam/tests/testTOAFactor.cpp b/gtsam_unstable/slam/tests/testTOAFactor.cpp
index 3227028e6..13a4b0996 100644
--- a/gtsam_unstable/slam/tests/testTOAFactor.cpp
+++ b/gtsam_unstable/slam/tests/testTOAFactor.cpp
@@ -36,11 +36,11 @@ public:
    * @param toaMeasurement time of arrival at microphone
    * @param model noise model
    */
-  TOAFactor(const Expression<Event>& event_,
+  TOAFactor(const Expression<Event>& eventExpression,
       const Expression<Point3>& microphone_, double toaMeasurement,
       const SharedNoiseModel& model) :
       ExpressionFactor<double>(model, toaMeasurement,
-          double_(&Event::toa, event_, microphone_)) {
+          double_(&Event::toa, eventExpression, microphone_)) {
   }
 
 };
@@ -60,7 +60,7 @@ using namespace gtsam;
 static const double ms = 1e-3;
 static const double cm = 1e-2;
 typedef Eigen::Matrix<double, 1, 1> Vector1;
-static SharedNoiseModel model(noiseModel::Isotropic::Sigma(1,0.5*ms));
+static SharedNoiseModel model(noiseModel::Isotropic::Sigma(1, 0.5 * ms));
 
 static const double timeOfEvent = 25;
 static const Event exampleEvent(timeOfEvent, 1, 0, 0);
@@ -69,10 +69,10 @@ static const Point3 microphoneAt0;
 //*****************************************************************************
 TEST( TOAFactor, Construct ) {
   Key key = 12;
-  Expression<Event> event_(key);
+  Expression<Event> eventExpression(key);
   Expression<Point3> knownMicrophone_(microphoneAt0); // constant expression
   double measurement = 7;
-  TOAFactor factor(event_, knownMicrophone_, measurement, model);
+  TOAFactor factor(eventExpression, knownMicrophone_, measurement, model);
 }
 
 //*****************************************************************************
@@ -88,7 +88,7 @@ TEST( TOAFactor, WholeEnchilada ) {
   microphones.push_back(Point3(403 * cm, 403 * cm, height));
   microphones.push_back(Point3(0, 403 * cm, height));
   EXPECT_LONGS_EQUAL(4, microphones.size());
-  microphones.push_back(Point3(200*cm, 200 * cm, height));
+  microphones.push_back(Point3(200 * cm, 200 * cm, height));
 
   // Create a ground truth point
   const double timeOfEvent = 0;
@@ -101,17 +101,18 @@ TEST( TOAFactor, WholeEnchilada ) {
     measurements[i] = groundTruthEvent.toa(microphones[i]);
     if (verbose) {
       cout << "mic" << i << " = " << microphones[i] << endl;
-      cout << "z" << i << " = " << measurements[i]/ms << endl;
+      cout << "z" << i << " = " << measurements[i] / ms << endl;
     }
   }
 
   // Now, estimate using non-linear optimization
   NonlinearFactorGraph graph;
   Key key = 12;
-  Expression<Event> event_(key);
+  Expression<Event> eventExpression(key);
   for (size_t i = 0; i < K; i++) {
     Expression<Point3> knownMicrophone_(microphones[i]); // constant expression
-    graph.add(TOAFactor(event_, knownMicrophone_, measurements[i], model));
+    graph.add(
+        TOAFactor(eventExpression, knownMicrophone_, measurements[i], model));
   }
 
   /// Print the graph
@@ -121,7 +122,8 @@ TEST( TOAFactor, WholeEnchilada ) {
   // Create initial estimate
   Values initialEstimate;
   //Event estimatedEvent(timeOfEvent -10, 200 * cm, 150 * cm, 350 * cm);
-  Vector4 delta; delta << 0.1, 0.1, -0.1, 0.1;
+  Vector4 delta;
+  delta << 0.1, 0.1, -0.1, 0.1;
   Event estimatedEvent = groundTruthEvent.retract(delta);
   initialEstimate.insert(key, estimatedEvent);
 
@@ -141,6 +143,74 @@ TEST( TOAFactor, WholeEnchilada ) {
 
   EXPECT(assert_equal(groundTruthEvent, result.at<Event>(key), 1e-6));
 }
+//*****************************************************************************
+/// Test real data
+TEST( TOAFactor, RealExperiment1 ) {
+
+  static const bool verbose = true;
+
+  // Create microphones
+  const double height = 0.5;
+  vector<Point3> microphones;
+  microphones.push_back(Point3(0, 0, height));
+  microphones.push_back(Point3(403 * cm, 0, height));
+  microphones.push_back(Point3(403 * cm, 403 * cm, height));
+  microphones.push_back(Point3(0, 403 * cm, height));
+  EXPECT_LONGS_EQUAL(4, microphones.size());
+
+  vector<Vector4> data(15);
+  size_t i = 0;
+  data[i++] << 1.2648, 1.2648, 1.2677, 1.2643;
+  data[i++] << 1.7329, 1.7347, 1.7354, 1.7338;
+  data[i++] << 2.2475, 2.2551, 2.2538, 2.2474;
+  data[i++] << 2.6945, 2.696, 2.6958, 2.694;
+  data[i++] << 3.1486, 3.152, 3.1513, 3.1501;
+  data[i++] << 3.6145, 3.611, 3.6076, 3.6067;
+  data[i++] << 4.1003, 4.1004, 4.099, 4.0972;
+  data[i++] << 4.5732, 4.568, 4.5667, 4.5722;
+  data[i++] << 5.0482, 5.0458, 5.0443, 5.0453;
+  data[i++] << 5.5311, 5.5256, 5.5254, 5.5305;
+  data[i++] << 5.9908, 5.9856, 5.9853, 5.9905;
+  data[i++] << 6.4575, 6.4524, 6.4527, 6.4579;
+  data[i++] << 6.8983, 6.8971, 6.8984, 6.9016;
+  data[i++] << 7.3581, 7.3524, 7.3538, 7.3588;
+  data[i++] << 7.8286, 7.8286, 7.8302, 7.8353;
+
+  // Create unknowns and initial estimate
+  Event nullEvent;
+  Values initialEstimate;
+  vector<Expression<Event> > eventExpressions;
+  for (size_t j = 0; j < 15; j++) {
+    initialEstimate.insert(j, nullEvent);
+    eventExpressions.push_back(Expression<Event>(j));
+  }
+
+  // Print
+  if (verbose)
+    initialEstimate.print("Initial Estimate:\n");
+
+  // Create factor graph and initial estimate
+  NonlinearFactorGraph graph;
+  for (size_t i = 0; i < 4; i++) {
+    Expression<Point3> mic_(microphones[i]); // constant expression
+    for (size_t j = 0; j < 15; j++)
+      graph.add(TOAFactor(eventExpressions[j], mic_, data[j][i], model));
+  }
+
+  /// Print the graph
+  if (verbose)
+    GTSAM_PRINT(graph);
+
+  // Optimize using Levenberg-Marquardt optimization.
+  LevenbergMarquardtParams params;
+  params.setAbsoluteErrorTol(1e-10);
+  if (verbose)
+    params.setVerbosity("ERROR");
+  LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, params);
+  Values result = optimizer.optimize();
+  if (verbose)
+    result.print("Final Result:\n");
+}
 
 //*****************************************************************************
 int main() {