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I've tried to optimize the LoRa setup using Arduino IDE libraries to ensure accurate or acceptable RSSI measurements and for distance estimation between multiple nodes and a master in an outdoor environment using those WiFi LoRa 32 V3 modules that operate within the frequency range of 433MHz ~ 510MHz with SX1262.

How do I implement signal processing techniques for consistent signal reception to optimize RSSI to minimal variation as a drone approaches different distances from nodes in outdoor localization using those WiFi LoRa 32 V3 modules spaced 400m apart?

Expectation: To ensure minimal variation in RSSI when the drone moves together with the master (y) approaches different distances from each node (x1, x2, x3) in the trilateration layout, as if under ideal outdoor conditions.

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    $\begingroup$ This is an interesting project for a research paper after a gew months of thought and experiments, but ill-posed for an short answer in a web forum. You want to.make statistical quantities consistent without defining what consistent means in this context. Ideal outdoor conditions in VHF/UHF is ill-defined as well, as you getbquite a bit of variation between desert/dry regions and water soaked ground. You also imply consistency independent of flight path, which is impossible. $\endgroup$
    – Andy Walls
    Commented Mar 8 at 13:06
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    $\begingroup$ Also for most hardware RSSI is not meaningful until you have synchronized to the incoming signal. If you lose lock on the received signal, RSSI values emitted from the hardware are just random garbage, so that cannot be made consistent when unlocked. $\endgroup$
    – Andy Walls
    Commented Mar 8 at 13:14
  • $\begingroup$ plus, LoRA is kind of a worst-case choice: Legally restricted to a very limited duty cycle, small integrated modules with completely unspecified antenna patters, typically transmit power highly dependent on supply voltage and hence dependent on battery state and lift in a drone. $\endgroup$ Commented Mar 8 at 13:29
  • $\begingroup$ @AndyWalls You're right. What "consistency" meant in the context is to find RSSI in a corrective range at every specific of known distance (e.g. 0-400m) and then essentially to achieve "close" distance estimation. As you pointed out, outdoor environments can vary significantly, and where it has been tested only at dorm corridor in 0-10m and will be further tested in the farming places, which are to meet the needs of most applications. $\endgroup$
    – Ausen
    Commented Mar 9 at 20:53
  • $\begingroup$ @AndyWalls Assuming consistent RSSI measurements independent of the drone's flight path is indeed unrealistic, in which I'm yet to be investigated, since the stabilization in accuracy data of the RSSI and distance measurements have not yet been completed. The formula that was applied as, float calculateDistance(int16_t rssi) { // Calibrated RSSI value at 1 meter (negative) float calibrated_rssi = -31; // Calculate distance based on average RSSI using calibrated RSSI at 1 meter float distance = (calibrated_rssi - rssi) / 20.0; return pow(10.0, distance);} $\endgroup$
    – Ausen
    Commented Mar 9 at 21:05

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