METHODS AND APPARATUS TO TRACK AND CLASSIFY OBJECTS

1 . An apparatus for use with an aircraft, the apparatus comprising:

interface circuitry communicatively coupled to an image sensor, the image sensor to capture images;

machine readable instructions; and

programmable circuitry to at least one of instantiate or execute the machine readable instructions to:

pre-process the images to identify potential targets;

filter, based on the identified potential targets, at least one of the images to determine a presence of a persistent object therein;

characterize a looming characteristic of the persistent object; and

classify the persistent object based on the looming characteristic meeting or exceeding a looming characteristic threshold.

2 . The apparatus of claim 1 , wherein the programmable circuitry is to determine a threat level of the persistent object based on the looming characteristic.

3 . The apparatus of claim 1 , wherein the programmable circuitry is to modify the looming characteristic threshold based on at least one of a size or a location of the persistent object.

4 . The apparatus of claim 1 , wherein the programmable circuitry is to track the persistent object, the programmable circuitry to characterize the looming characteristic in response to the tracking of the persistent object.

5 . The apparatus of claim 1 , wherein the programmable circuitry is to classify the persistent object via a machine learning model, the machine learning model trained with classification information of known objects.

6 . The apparatus of claim 5 , wherein the programmable circuitry is to:

characterize the persistent object based on the looming characteristic; and

train the machine learning model in response to characterizing the persistent object.

7 . The apparatus of claim 1 , wherein the programmable circuitry is to determine a persistence of the persistent object based on an object size being one pixel.

8 . The apparatus of claim 1 , wherein the programmable circuitry is to determine a persistence of the persistent object based on a rate of change of an object size.

9 . A non-transitory machine readable storage medium comprising instructions to cause programmable circuitry to at least:

pre-process an image to identify potential targets;

filter, based on the identified potential targets, at least one of the images to determine a presence of a persistent object therein;

characterize a looming characteristic of the persistent object; and

classify the persistent object based on the looming characteristic meeting or exceeding a looming characteristic threshold.

10 . The non-transitory machine readable storage medium of claim 9 , wherein the instructions cause the programmable circuitry to determine a threat level of the persistent object based on the looming characteristic.

11 . The non-transitory machine readable storage medium of claim 9 , wherein the instructions cause the programmable circuitry to modify the looming characteristic threshold based on at least one of a size or a location of the persistent object.

12 . The non-transitory machine readable storage medium of claim 9 , wherein the instructions cause the programmable circuitry to track the persistent object, wherein the looming characteristic is characterized in response to the tracking of the persistent object.

13 . The non-transitory machine readable storage medium of claim 9 , wherein the instructions cause the programmable circuitry to classify the persistent object via a machine learning model, the machine learning model trained with classification information of known objects.

14 . The non-transitory machine readable storage medium of claim 13 , wherein the instructions cause the programmable circuitry to:

characterize the persistent object based on the looming characteristic; and

train the machine learning model in response to characterizing the persistent object.

15 . The non-transitory machine readable storage medium of claim 9 , wherein the instructions cause the programmable circuitry to determine a persistence of the persistent object based on an object size being one pixel.

16 . The non-transitory machine readable storage medium of claim 9 , wherein the instructions cause the programmable circuitry to determine a persistence of the persistent object based on a rate of change of an object size.

17 . A method comprising:

pre-processing, by executing instructions with processor circuitry, an image to identify potential targets;

filtering, by executing instructions with the processor circuitry, at least one of the images based on the identified potential targets to determine a presence of a persistent object therein;

characterizing, by executing instructions with the processor circuitry, a looming characteristic of the persistent object; and

classifying, by executing instructions with the processor circuitry, the persistent object based on the looming characteristic meeting or exceeding a looming characteristic threshold.

18 . The method of claim 17 , further including determining, by executing instructions with the processor circuitry, a threat level of the persistent object based on the looming characteristic.

19 . The method of claim 17 , further including tracking, by executing instructions with the processor circuitry, the persistent object, the characterizing of the looming characteristic in response to the tracking of the persistent object.

20 . The method of claim 17 , wherein classifying of the persistent object is performed via a machine learning model, the machine learning model trained with classification information of known objects.