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Update readme and minor fixes
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6 changed files with 31 additions and 14 deletions
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@ -2,6 +2,10 @@
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Target localisation for multi-static radar using ellipse intersections. Not a dating app.
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See a live instance at [http://3lips.30hours.dev](http://3lips.30hours.dev).
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![3lips example display](./example.png "3lips")
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## Features
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- Provides a JSON API for geolocation of targets given [blah2](http://github.com/30hours/blah2) radar nodes.
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@ -12,6 +16,7 @@ Target localisation for multi-static radar using ellipse intersections. Not a da
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- Install docker and docker-compose on the host machine.
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- Clone this repository to some directory.
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- Edit the [./config/config.yml](./config./config.yml) file for scenario.
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- Run the docker compose command.
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```bash
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@ -46,6 +51,7 @@ The system architecture is as follows:
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- Implement an association algorithm that is not reliant on ADS-B truth.
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- Choose to use detection or track data from each radar.
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- Long term plots to show metrics such as 2D location accuracy to ADS-B, number of aircraft tracked, etc.
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- Scale number of samples in ellipse/ellipsoid to size of shape.
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## License
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@ -20,7 +20,7 @@ function event_ellipsoid() {
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removeEntitiesByType("ellipsoids");
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}
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else {
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removeEntitiesOlderThanAndFade("ellipsoids", 5, 0.5);
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removeEntitiesOlderThanAndFade("ellipsoids", 10, 0.5);
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}
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for (const key in data["ellipsoids"]) {
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if (data["ellipsoids"].hasOwnProperty(key)) {
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@ -54,7 +54,7 @@ function event_ellipsoid() {
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}
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var style_ellipsoid = {};
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style_ellipsoid.color = 'rgba(0, 0, 255, 0.5)';
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style_ellipsoid.color = 'rgba(0, 255, 255, 0.5)';
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style_ellipsoid.pointSize = 16;
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style_ellipsoid.type = "ellipsoids";
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style_ellipsoid.timestamp = Date.now();
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@ -16,7 +16,7 @@ function event_radar() {
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return;
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}
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removeEntitiesOlderThanAndFade("detection", 90, 0.5);
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removeEntitiesOlderThanAndFade("detection", 10, 0.5);
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for (const key in data["detections_localised"]) {
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if (data["detections_localised"].hasOwnProperty(key)) {
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@ -31,8 +31,8 @@ tDelete = 60
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adsbAssociator = AdsbAssociator()
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ellipseParametricMean = EllipseParametric("mean", 150, 500)
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ellipseParametricMin = EllipseParametric("min", 150, 500)
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ellipsoidParametricMean = EllipsoidParametric("mean", 120, 1000)
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ellipsoidParametricMin = EllipsoidParametric("min", 120, 1000)
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ellipsoidParametricMean = EllipsoidParametric("mean", 60, 800)
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ellipsoidParametricMin = EllipsoidParametric("min", 60, 800)
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sphericalIntersection = SphericalIntersection()
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adsbTruth = AdsbTruth(5)
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save = True
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@ -40,7 +40,7 @@ saveFile = '/app/save/' + str(int(time.time())) + '.ndjson'
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async def event():
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start_time = time.time()
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print('Start event', flush=True)
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global api, save
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timestamp = int(time.time()*1000)
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@ -101,6 +101,8 @@ async def event():
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# main processing
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for item in api_event:
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start_time = time.time()
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# extract dict for item
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radar_dict_item = {
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key: radar_dict[key]
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@ -196,6 +198,9 @@ async def event():
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item["ellipsoids"] = ellipsoids
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item["time"] = stop_time - start_time
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print('Method: ' + item["localisation"], flush=True)
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print(item["time"], flush=True)
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# delete old API requests
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api_event = [
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item for item in api_event if timestamp - item["timestamp"] <= tDelete*1000]
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@ -234,7 +239,7 @@ def short_hash(input_string, length=10):
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# message received callback
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async def callback_message_received(msg):
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print(f"Callback: Received message in event.py: {msg}", flush=True)
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#print(f"Callback: Received message in event.py: {msg}", flush=True)
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timestamp = int(time.time()*1000)
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BIN
example.png
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BIN
example.png
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After Width: | Height: | Size: 1.1 MiB |
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@ -164,20 +164,26 @@ def main():
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# plot x, y, z
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#plt.figure(figsize=(5,7))
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position2 = {}
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position2["ellipse-parametric-mean"] = position["ellipse-parametric-mean"]
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position2["ellipsoid-parametric-mean"] = position["ellipsoid-parametric-mean"]
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position2["spherical-intersection"] = position["spherical-intersection"]
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mark = ['x', 'o', 's']
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position_reord = ["ellipse-parametric-mean", "ellipsoid-parametric-mean", "spherical-intersection"]
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fig, axes = plt.subplots(3, 1, figsize=(5, 7), sharex=True)
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for i in range(3):
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yaxis_truth = [pos[i] for pos in truth_position_resampled_enu]
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plt.subplot(3, 1, i+1)
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plt.plot(timestamp, yaxis_truth, label="ADS-B Truth")
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for method in position:
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for method in position_reord:
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print(position[method])
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if "detections_enu" not in position[method]:
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continue
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for i in range(3):
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print(position)
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#print(position)
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yaxis_target = [pos[i] for pos in position[method]["detections_enu"]]
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plt.subplot(3, 1, i+1)
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plt.plot(position[method]["timestamp"], yaxis_target, 'x', label=method)
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plt.plot(position[method]["timestamp"], yaxis_target, marker=mark[i], label=method)
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plt.xlabel('Timestamp')
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if i == 0:
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plt.ylabel('ENU X (m)')
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plt.ylabel('ENU Z (m)')
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plt.subplot(3, 1, 1)
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plt.legend()
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plt.legend(prop = {"size": 8})
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plt.tight_layout()
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filename = 'plot_accuracy_' + args.target_name + '.png'
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plt.savefig('save/' + filename, bbox_inches='tight', pad_inches=0.01)
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@ -206,9 +212,9 @@ def main():
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yaxis_target = [pos[i] for pos in position[method]["detections_enu"]]
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table[method][str(i)] = calculate_rmse(yaxis_target, yaxis_truth_target)
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print('test')
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print(yaxis_target)
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print(yaxis_truth_target)
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#print('test')
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#print(yaxis_target)
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#print(yaxis_truth_target)
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print(table)
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