Acquiring information regarding a volume using wireless networks

• US 10,405,222 B2
• Filed: 02/10/2017
• Issued: 09/03/2019
• Est. Priority Date: 10/18/2012
• Status: Active Grant

• Current Assignee: Gil Zwirn
• Original Assignee: Gil Zwirn
• Inventors: Zwirn, Gil
• Primary Examiner(s): Le, Thanh C
• Application Number:
  US15/430,033
• Publication Number:
  US 20170164227A1
• Time in Patent Office: 935 Days
• CPC Class Codes: H04W 24/10 Scheduling measurement reports ; Arrangements for measurement reports

Abstract

There is provided a method for acquiring information regarding terrain and/or objects within a volume, said method comprising: transmitting signals over time (“node signals”) from one or more nodes of a wireless network (“subject network”); receiving the node signals after their traversing a medium (“node resultant signals”) using one or more receiving units (“node signal receivers”); measuring one or more physical attributes (“signal attributes”) for one or more of the node resultant signals, wherein at least one of the signal attributes is of at least one of the following types: (a) time difference between node signal transmission by the applicable transmitting subject network node and node resultant signal reception by the applicable node signal receiver; (b) phase difference between the transmitted node signal and the received node resultant signal; (c) power ratio between the transmitted node signal and the received node resultant signal; (d) frequency difference between the received node resultant signal and the transmitted node signal (Doppler shift); and/or (e) direction from which the node resultant signal has arrived, and/or its projection on one or more predefined axes; estimating the spatial location as a function of time for one or more of the transmitting subject network nodes and/or one or more of the node signal receivers; and analyzing one or more of the node resultant signals and/or one or more of the signal attributes to extract information regarding objects along the signal'"'"'s paths (“mapping information”).

Claims

1. A method for traffic and/or parking monitoring using signals transmitted by wireless networks, said method comprising:

receiving node signals transmitted by one or more nodes of wireless networks using one or more node signal receivers, wherein the node signals comprise node resultant signals received after traversing a medium, and wherein each of the one or more node signal receivers is configured to receive signals associated with one or more transmitting subject network nodes;

detecting and tracking objects within a target volume, by applying the following processing steps to the received node resultant signals;

a. for each node signal receiver, applying matched filtering between the received node resultant signal and one or more waveforms of the transmitting subject network nodes, to obtain matched node resultant signals;

b. for each matched node resultant signal, applying object detection and outputting a detected object record, and for each output of object detection, measuring one or more physical parameters;

c. if possible, associating one or more of the outputs of object detection with one or more of the following;

i. other outputs of object detection, expected to correspond to the same physical object within the target volume, wherein the other outputs of object detection relate to a different node signal receiver and/or a different transmitting subject network node;

ii. outputs of object detection produced at an earlier time, expected to correspond to the same physical object within the target volume, wherein the outputs of object detection may relate to any node signal receiver and/or any transmitting subject network node; and

iii. outputs of object compounding produced at an earlier time, expected to correspond to the same physical object within the target volume; and

d. for each association, compounding the physical parameter measurements relating to the corresponding object records and outputting a compounded object record, in order to obtain additional or more precise information regarding the corresponding physical object within the target volume.

2. The method according to claim 1, wherein the detecting and tracking objects within the target volume further comprises one or more of the following:

a. for one or more object records, analyzing the associated physical parameter measurements to obtain object classification and/or recognition; and

b. discarding object records whose classification and/or recognition outputs are irrelevant for vehicle monitoring.

3. The method according to claim 1, wherein any of the waveforms of the transmitting subject network nodes may be one or more of the following:

a. fully known in advance;

b. partially known in advance, wherein only the part known in advance is used for the matched filtering;

c. partially known in advance, wherein the unknown part or certain portions thereof are estimated based on a communication protocol used by the transmitting subject network node; and

d. not known in advance, and partially or fully estimated based on a communication protocol used by the transmitting subject network node.

4. The method according to claim 1, wherein applying object detection comprises applying a global and/or a local energy threshold to the matched node resultant signal.

5. The method according to claim 1, wherein applying object detection comprises:

a. producing a range-Doppler map, by doing the following;

i. selecting node sequences, comprising several consecutive transmission sequences of the transmitting subject network node, for matched filtering;

ii. for each node sequence, arranging the matched node resultant signal as a function of time, the arranged matched node resultant signal comprising range-gate samples, and having corresponding sample range-gate indices; and

iii. for each range-gate index, applying a discrete Fourier transform to the corresponding range-gates of the arranged matched node resultant signals over all selected node sequences, outputting range-Doppler map

b. applying a global and/or local energy threshold to the range-Doppler map.

6. The method according to claim 1, wherein one or more of the measured physical parameters includes information regarding one or more of the following:

a. the object'"'"'s location;

b. the object'"'"'s orientation;

c. the object'"'"'s dynamic properties;

d. the object'"'"'s spatial dimensions; and

e. the object'"'"'s reflection cross-section model.

7. The method according to claim 1, wherein the association of one or more of the outputs of object detection comprises looking for objects with sufficiently similar attributes.

8. The method according to claim 7, wherein one or more of the attributes used for association includes one or more of the following:

a. a parameter relating to spatial location, in any coordinate system;

b. a parameter relating to the velocity vector or projections thereof, in any coordinate system;

c. a parameter relating to spatial dimensions, or projections thereof; and

d. a parameter relating to the reflection cross-section model.

9. The method according to claim 1, wherein the compounding of the physical parameter measurements comprises one or more of the following:

a. using multi-lateration to improve the assessment of object'"'"'s spatial location and/or dynamic properties based on information associated with different transmitting subject network nodes and/or different node signal receivers;

b. using projections of the object'"'"'s spatial dimensions, made by multiple transmitting subject network nodes and/or multiple node signal receivers, to improve the object'"'"'s spatial dimensions estimation; and

c. using reflection cross-section measurements made using multiple transmitting subject network nodes and/or multiple node signal receivers to estimate one or more parameters relating to the object'"'"'s reflection cross-section model.

10. The method according to claim 1, wherein the compounding of the physical parameter measurements comprises one or more of the following:

a. using a filter to estimate the behavior of some of the object'"'"'s attributes as a function of time; and

b. using a pattern recognition method to analyze the object'"'"'s dynamic behavior over time.

11. The method according to claim 1, further comprising performing on the outputs of detecting and tracking objects within the target volume, or certain functions thereof, one or more of the following:

a. storing in a database; and

b. displaying to one or more users.

12. The method according to claim 1, further comprising performing on the outputs of detecting and tracking objects within the target volume one or more of the following:

a. traffic analysis, providing information regarding the distribution of vehicle location and/or velocity as a function of space and time;

b. traffic analysis, providing information regarding traffic accidents and/or traffic law violations;

c. parking analysis, providing information regarding occupied, vacant, and/or soon to be vacant parking spots; and

d. parking analysis, providing information regarding illegally parked vehicles.

13. A method for traffic and/or parking monitoring using signals transmitted by wireless networks, said method comprising:

receiving node signals transmitted by one or more nodes of wireless networks using one or more node signal receivers, wherein the node signals comprise mpde resultant signals received after traversing a medium, and wherein each of the one or more node signal receivers is configured to receive signals associated with one or more transmitting subject network nodes;

detecting and tracking objects within a target volume, by applying the following processing steps;

a. at certain time increments, applying an inverse problem method to the received node resultant signal, to obtain target volume maps;

b. applying image processing to the target volume maps, to detect objects within them, and for each detected object, extract one or more physical attributes;

c. if possible, associating detected objects in different volume maps, expected to correspond to the same physical object within the target volume, wherein the different volume maps relate to different times; and

d. for each association result, compounding the physical attributes relating to the corresponding detected objects, in order to obtain additional and/or more precise information regarding the objects.

14. The method according to claim 13, wherein the detecting and tracking objects within the target volume further comprises one or more of the following:

a. for one or more detected objects, analyzing the associated physical attributes before or after compounding, to obtain object classification and/or recognition; and

b. discarding detected objects whose classification and/or recognition outputs are irrelevant for vehicle monitoring.

15. The method according to claim 13, wherein the image processing applied to the target volume maps to detect objects within them is based on one or more of the following:

a. applying a local and/or a global threshold to the power of the target volume maps;

b. automatic recognition of various object types using automatic target recognition (ATR) methods; and

c. motion detection, by arranging the target volume maps in accordance with their acquisition time and applying change detection algorithms.

16. The method according to claim 13, wherein the one or more physical attributes include one or more of the following:

a. parameters relating to spatial location;

b. parameter relating to orientation;

c. parameters relating to dynamic properties;

d. spatial dimensions, or projections thereof; and

e. parameters relating to the reflection cross-section model.

17. The method according to claim 13, wherein the association of detected objects in different volume maps comprises looking for objects with sufficient similarity in one or more of the physical attributes.

18. The method according to claim 13, wherein the compounding of the physical attributes comprises one or more of the following:

a. using a filter to estimate the behavior of some of the object'"'"'s attributes as a function of time; and

b. using a pattern recognition method to analyze the object'"'"'s dynamic behavior over time.

19. The method according to claim 13, further comprising performing on the outputs of detecting and tracking objects within the target volume, or certain functions thereof, one or more of the following:

a. storing in a database; and

b. displaying to one or more users.

20. The method according to claim 13, further comprising performing on the outputs of detecting and tracking objects within the target volume one or more of the following:

a. traffic analysis, providing information regarding the distribution of vehicle location and/or velocity as a function of space and time;

b. traffic analysis, providing information regarding traffic accidents and/or traffic law violations;

c. parking analysis, providing information regarding occupied, vacant, and/or soon to be vacant parking spots; and

d. parking analysis, providing information regarding illegally parked vehicles.