TD2: GNSS-like systems

This TD uses the data structures from TD1.

Access Points data

You will add an AccessPoint class with the desired members to build and access AP data. Your class is based on the following fields:

class AccessPoint:
	def __init__(self, mac: str, loc=Location(): Location, p=20.0: float, a=5.0: float, f=2417000000: float):
		self.mac_address = mac
		self.location = loc
		self.output_power_dbm = p
		self.antenna_dbi = a
		self.output_frequency_hz = f

AP data will be static, such like this:

AP = {"00:13:ce:95:e1:6f": AccessPoint("00:13:ce:95:e1:6f", 4.93, 25.81, 3.55, 2417000000, 5.0, 20.0), \
      "00:13:ce:95:de:7e": AccessPoint("00:13:ce:95:de:7e", 4.83, 10.88, 3.78, 2417000000, 5.0, 20.0), \
      "00:13:ce:97:78:79": AccessPoint("00:13:ce:97:78:79", 20.05, 28.31, 3.74, 2417000000, 5.0, 20.0), \
      "00:13:ce:8f:77:43": AccessPoint("00:13:ce:8f:77:43", 4.13, 7.085, 0.80, 2417000000, 5.0, 20.0), \
      "00:13:ce:8f:78:d9": AccessPoint("00:13:ce:8f:78:d9", 5.74, 30.35, 2.04, 2417000000, 5.0, 20.0)}

Computing FBCM index

In this part, you have to compute the FBCM index given a distance between a transmitter and a receiver, and its RSSISample.

def compute_FBCM_index(distance: float, rssi_values: RSSISample, ap: AccessPoint) -> float:
	"""
    Function compute_FBCM_index computes a FBCM index based on the distance (between transmitter and receiver)
    and the AP parameters. We consider the mobile device's antenna gain is 2.1 dBi.
    :param distance: the distance between AP and device
    :param rssi_values: the RSSI values associated to the AP for current calibration point. Use their average value.
    :return: one value for the FBCM index
    """
	pass

Computing a distance based on a RSSISample

Here, you have to implement the following function, which takes an average RSSI value for a transmitter and a receiver, a FBCM index matching the sample and the corresponding AP data. Consider a 2.1 dBi gain for the device.

def estimate_distance(rssi_avg: float, fbcm_index: float, ap: AccessPoint) -> float:
    """
    Function estimate_distance estimates the distance between an access point and a test point based on
    the test point rssi sample.
    :param rssi: average RSSI value for test point
    :param fbcm_index: index to use
    :param ap: access points parameters used in FBCM
    :return: the distance (meters)
    """
	pass

Getting a location

With distances between a device and at least 3 references, compute device's location. You may use grid search, or python solver (least squares, etc.)

def multilateration(distances: dict[str, float], ap_locations: dict[str, Location]) -> Location:
    """
    Function multilateration computes a location based on its distances towards at least 3 access points
    :param distances: the distances associated to the related AP MAC addresses as a string
    :param ap_locations: the access points locations, indexed by AP MAC address as strings
    :return: a location
    """
	pass

Main

Use all functions to provide compute locations for the test data set provided with these instructions (calibration data will be TD1 data).