Active signal detection using adaptive identification of a noise floor
A device can accurately discriminate an active pulse from noise by setting a dynamic noise floor that adjusts according to environmental conditions. For example, the device may discriminate, as the active pulse, a light pulse emitted by a light emitter of the system and reflected off an object to a light sensor, from noise such as sunlight glare by determining a dynamic noise floor and identifying, as an active pulse, at least a portion of the received signal that exceeds the dynamic noise floor for a threshold number of samples. The dynamic noise floor may be determined, for example, using a moving average of the received signal and/or shifting or scaling the noise floor based on other properties of the return signal.
1. A non-transitory computer-readable medium storing instructions that, when executed, cause one or more processors to perform operations comprising:
causing a light emitter to emit a light pulse;
discriminating a return pulse from noise in a signal received at a light sensor, the return pulse including light from a reflection of the light pulse and noise; and
determining a distance to an object that reflected at least part of the light pulse to the light sensor based, at least in part, on a delay between emitting the light pulse and a time associated with receiving the return pulse at the light sensor, wherein discriminating the return pulse from the noise in the received signal includes:
determining a noise floor, determining the noise floor including:
determining a moving average of a magnitude of the received signal; and
at least one of shifting or scaling the moving average based, at least in part, on at least one property of the received signal;
determining a number of samples of the received signal associated with a magnitude exceeding the noise floor;
determining that the number of samples exceeds a threshold number; and
indicating, based, at least in part, on the determination that the number of samples exceeds the threshold number, that the samples that exceed the noise floor are indicative of the return pulse.
2. The non-transitory computer-readable medium as claim 1 recites, wherein the threshold number is a first threshold number, and the operations further comprising:
determining that the number of the samples exceeds a second threshold number, the second threshold number being greater than the first threshold number; and
based, at least in part, on determining that the threshold number or more of the samples exceeds the threshold magnitude, identifying the return pulse as a saturated signal.
3. The non-transitory computer-readable medium as claim 2 recites, the operations further comprising based, at least in part, on the identification, determining the distance based, at least in part, on a rising edge of the return pulse.
4. The non-transitory computer-readable medium as claim 1 recites, wherein the threshold number is a first threshold number, and the operations further comprising:
determining that the number of the samples does not meet a second threshold number; and
based, at least in part, on determining that the number of the samples are less than the second threshold number, identifying the return pulse as an unsaturated signal.
5. The non-transitory computer-readable medium as claim 4 recites, the operations further comprising based, at least in part, on the identification, determining the distance based, at least in part, on correlating the return pulse with a reference signal.
6. A computer-implemented method comprising:
receiving a signal indicating light received at a light sensor, the signal discretized as a series of samples;
determining a noise floor based, at least in part, on determining a moving average of the signal;
determining a number of samples of the signal that exceed the noise floor; and
determining, based, at least in part, on the number of samples, that the signal comprises an active return pulse or exclusively comprises noise.
7. The computer-implemented method as claim 6 recites, further comprising determining a distance based, at least in part, on the signal and determining that the signal comprises an active return pulse.
8. The computer-implemented method as claim 6 recites, further comprising:
determining that one or more samples of the signal do not exceed the noise floor; and
identifying the one or more samples as noise.
9. The computer-implemented method as claim 6 recites, wherein determining that the signal comprises an active return pulse further includes determining that the number of samples exceeds a threshold number.
10. The computer-implemented method as claim 9 , wherein the threshold number is a first threshold number and the method further comprising:
determining that the signal is saturated based, at least in part, on determining that the number of samples exceeds a second threshold number, the second threshold number being greater than the first threshold number; or
determining that the signal is unsaturated based, at least in part, on determining that the number of samples does not meet the second threshold number.
11. The computer-implemented method as claim 6 recites, wherein determining the moving average includes determining a sum of 10% of the current magnitude and 90% of the previous moving average.
12. The computing-implemented method as claim 6 recites, wherein determining the noise floor additionally includes at least one of vertically shifting the moving average or scaling the moving average based, at least in part, on at least one property of the signal.
13. The computing-implemented method as claim 12 recites, wherein the at least one property includes a magnitude of the signal.
14. The computing-implemented method as claim 6 recites, further comprising discarding the signal based, at least in part, on determining that the signal exclusively comprises noise.
15. A system comprising:
a light sensor;
one or more processors; and
one or more computer-readable media storing instructions executable by the one or more processors, wherein the instructions program the one or more processors to:
receive a signal indicative of light received at the light sensor, the signal discretized as a sequence of samples;
generate a noise floor based, at least in part on the signal;
determine that a number of samples associated with magnitudes that exceed a threshold number;
determine a time delay of arrival from the signal; and
determine a distance based, at least in part, on the time delay of arrival.
16. The system as claim 15 recites, wherein generating the noise floor includes determining a moving average.
17. The system as claim 16 recites, wherein the moving average weights the previous magnitude more heavily than a weight of the current magnitude.
18. The system as claim 16 recites, wherein generating the noise floor additionally includes at least one of vertically shifting the moving average or scaling the moving average based, at least in part, on at least one property of the signal.
19. The system as claim 18 recites, wherein the at least one property includes a magnitude of the signal.
20. The system as claim 16 recites, wherein generating the noise floor additionally includes scaling the moving average based, at least in part, on a magnitude of the signal, the scale increasing in proportion to the magnitude.