Update readme and minor fixes

README.md

@@ -2,6 +2,10 @@
 
 Target localisation for multi-static radar using ellipse intersections. Not a dating app.
 
+See a live instance at [http://3lips.30hours.dev](http://3lips.30hours.dev).
+
+![3lips example display](./example.png "3lips")
+
 ## Features
 
 - Provides a JSON API for geolocation of targets given [blah2](http://github.com/30hours/blah2) radar nodes.
@@ -12,6 +16,7 @@ Target localisation for multi-static radar using ellipse intersections. Not a da
 
 - Install docker and docker-compose on the host machine.
 - Clone this repository to some directory.
+- Edit the [./config/config.yml](./config./config.yml) file for scenario.
 - Run the docker compose command.
 
 ```bash
@@ -46,6 +51,7 @@ The system architecture is as follows:
 - Implement an association algorithm that is not reliant on ADS-B truth.
 - Choose to use detection or track data from each radar.
 - Long term plots to show metrics such as 2D location accuracy to ADS-B, number of aircraft tracked, etc.
+- Scale number of samples in ellipse/ellipsoid to size of shape.
 
 ## License
 

api/map/event/ellipsoid.js

@@ -20,7 +20,7 @@ function event_ellipsoid() {
       removeEntitiesByType("ellipsoids");
     }
     else {
-      removeEntitiesOlderThanAndFade("ellipsoids", 5, 0.5);
+      removeEntitiesOlderThanAndFade("ellipsoids", 10, 0.5);
     }
     for (const key in data["ellipsoids"]) {
       if (data["ellipsoids"].hasOwnProperty(key)) {
@@ -54,7 +54,7 @@ function event_ellipsoid() {
 }
 
 var style_ellipsoid = {};
-style_ellipsoid.color = 'rgba(0, 0, 255, 0.5)';
+style_ellipsoid.color = 'rgba(0, 255, 255, 0.5)';
 style_ellipsoid.pointSize = 16;
 style_ellipsoid.type = "ellipsoids";
 style_ellipsoid.timestamp = Date.now();

api/map/event/radar.js

@@ -16,7 +16,7 @@ function event_radar() {
       return;
     }
 
-    removeEntitiesOlderThanAndFade("detection", 90, 0.5);
+    removeEntitiesOlderThanAndFade("detection", 10, 0.5);
 
     for (const key in data["detections_localised"]) {
       if (data["detections_localised"].hasOwnProperty(key)) {

event/event.py

@@ -31,8 +31,8 @@ tDelete = 60
 adsbAssociator = AdsbAssociator()
 ellipseParametricMean = EllipseParametric("mean", 150, 500)
 ellipseParametricMin = EllipseParametric("min", 150, 500)
-ellipsoidParametricMean = EllipsoidParametric("mean", 120, 1000)
+ellipsoidParametricMean = EllipsoidParametric("mean", 60, 800)
-ellipsoidParametricMin = EllipsoidParametric("min", 120, 1000)
+ellipsoidParametricMin = EllipsoidParametric("min", 60, 800)
 sphericalIntersection = SphericalIntersection()
 adsbTruth = AdsbTruth(5)
 save = True
@@ -40,7 +40,7 @@ saveFile = '/app/save/' + str(int(time.time())) + '.ndjson'
 
 async def event():
 
-    start_time = time.time()
+    print('Start event', flush=True)
 
     global api, save
     timestamp = int(time.time()*1000)
@@ -101,6 +101,8 @@ async def event():
     # main processing
     for item in api_event:
 
+      start_time = time.time()
+
       # extract dict for item
       radar_dict_item =  {
           key: radar_dict[key] 
@@ -196,6 +198,9 @@ async def event():
       item["ellipsoids"] = ellipsoids
       item["time"] = stop_time - start_time
 
+      print('Method: ' + item["localisation"], flush=True)
+      print(item["time"], flush=True)
+
     # delete old API requests
     api_event = [
       item for item in api_event if timestamp - item["timestamp"] <= tDelete*1000]
@@ -234,7 +239,7 @@ def short_hash(input_string, length=10):
 # message received callback
 async def callback_message_received(msg):
 
-    print(f"Callback: Received message in event.py: {msg}", flush=True)
+    #print(f"Callback: Received message in event.py: {msg}", flush=True)
 
     timestamp = int(time.time()*1000)
 

script/plot_accuracy.py

@@ -164,20 +164,26 @@ def main():
 
     # plot x, y, z
     #plt.figure(figsize=(5,7))
+    position2 = {}
+    position2["ellipse-parametric-mean"] = position["ellipse-parametric-mean"]
+    position2["ellipsoid-parametric-mean"] = position["ellipsoid-parametric-mean"]
+    position2["spherical-intersection"] = position["spherical-intersection"]
+    mark = ['x', 'o', 's']
+    position_reord = ["ellipse-parametric-mean", "ellipsoid-parametric-mean", "spherical-intersection"]
     fig, axes = plt.subplots(3, 1, figsize=(5, 7), sharex=True)
     for i in range(3):
         yaxis_truth = [pos[i] for pos in truth_position_resampled_enu]
         plt.subplot(3, 1, i+1)
         plt.plot(timestamp, yaxis_truth, label="ADS-B Truth")
-    for method in position:
+    for method in position_reord:
         print(position[method])
         if "detections_enu" not in position[method]:
           continue
         for i in range(3):
-            print(position)
+            #print(position)
             yaxis_target = [pos[i] for pos in position[method]["detections_enu"]]
             plt.subplot(3, 1, i+1)
-            plt.plot(position[method]["timestamp"], yaxis_target, 'x', label=method)
+            plt.plot(position[method]["timestamp"], yaxis_target, marker=mark[i], label=method)
             plt.xlabel('Timestamp')
             if i == 0:
                 plt.ylabel('ENU X (m)')
@@ -187,7 +193,7 @@ def main():
                 plt.ylabel('ENU Z (m)')
     
     plt.subplot(3, 1, 1)
-    plt.legend()
+    plt.legend(prop = {"size": 8})
     plt.tight_layout()
     filename = 'plot_accuracy_' + args.target_name + '.png'
     plt.savefig('save/' + filename, bbox_inches='tight', pad_inches=0.01)
@@ -206,9 +212,9 @@ def main():
             
             yaxis_target = [pos[i] for pos in position[method]["detections_enu"]]
             table[method][str(i)] = calculate_rmse(yaxis_target, yaxis_truth_target)
-            print('test')
+            #print('test')
-            print(yaxis_target)
+            #print(yaxis_target)
-            print(yaxis_truth_target)
+            #print(yaxis_truth_target)
 
     print(table)