초록 ▼

A system and method is presented for detecting and classifying slow-moving and hovering helicopters from a missile's look-down Doppler radar that is compatible with the existing base of Doppler radars. This approach uses definable attributes of a helicopter rotor assembly and its extended Doppler ro

A system and method is presented for detecting and classifying slow-moving and hovering helicopters from a missile's look-down Doppler radar that is compatible with the existing base of Doppler radars. This approach uses definable attributes of a helicopter rotor assembly and its extended Doppler rotor return to differentiate "rotor samples" from other samples (steps 123, 125), extract features such as bandwidth, activity, angle, and shape from the rotor samples (step 127), and classify a potential target as a helicopter or other based on the extracted rotor features and the known attributes of the helicopter rotor assembly (step 129). A target report including a classification target, range, range-rate, and angle of the extended rotor return is suitably passed to a tracking processor (step 121).

대표청구항 ▼

We claim: 1. A method of missile radar tracking helicopters, comprising: receiving on-board missile radar samples having an amplitude and Doppler shift that define a Doppler map including ground clutter, body and extended rotor returns; detecting a potential target in the Doppler map; defining at l

We claim: 1. A method of missile radar tracking helicopters, comprising: receiving on-board missile radar samples having an amplitude and Doppler shift that define a Doppler map including ground clutter, body and extended rotor returns; detecting a potential target in the Doppler map; defining at least one search window that excludes ground clutter and body returns and includes at least a portion of the extended rotor return; setting a threshold above a constant false-alarm rate (CFAR) threshold; comparing the samples within said at least one search window to the threshold to identify rotor samples; extracting rotor features from the rotor samples; and classifying the potential target as a helicopter or other based on the extracted rotor features and known attributes of a helicopter rotor assembly. 2. The method of claim 1, wherein a pair of said search windows are defined to capture portions of the extended rotor return on either side of the clutter return. 3. The method of claim 1, wherein a single said search window is defined to capture a portion of the extended rotor return on the side of the body return opposite the ground clutter. 4. The method of claim 1 wherein at least one search window has a minimum Doppler shift that is set to exclude ground clutter and body returns and a maximum Doppler shift that is set to include the bandwidth of the extended rotor return. 5. The method of claim 1, wherein the threshold is set to the greater of a predetermined increment above the CFAR threshold or a predetermined amount below the peak of the body return. 6. The method of claim 1, wherein the CFAR threshold is varied over time to maintain a constant false-alarm rate. 7. The method of claim 1, wherein the radar samples are extracted from pulses at multiple range gates. 8. The method of claim 1, further comprising: providing a target report including a classification tag, a range and a range-rate for the helicopter. 9. A method of missile radar tracking helicopters, comprising: receiving on-board missile radar samples having an amplitude and Doppler shift that define a Doppler map including ground clutter, body and extended rotor returns; detecting a potential target in the Doppler map; identifying rotor samples from samples within the extended rotor return; extracting rotor features from the rotor samples including determining a bandwidth of the extended rotor return and determining an activity measure that estimates a fraction of samples within the bandwidth identified as rotor samples; and classifying the potential target as a helicopter or other based on the extracted rotor features and known attributes of a helicopter rotor assembly. 10. The method of claim 9, wherein extracting rotor features further includes extracting an angle for each rotor sample. 11. The method of claim 10, wherein extracting rotor features further includes computing a uniformity metric for the angles of the rotor samples. 12. The method of claim 9, wherein extracting rotor features further includes extracting a shape feature of the amplitudes of the rotor samples within the bandwidth of the extended rotor return. 13. A method of missile radar tracking helicopters, comprising: receiving on-board missile radar samples having an amplitude and Doppler shift for multiple range gates that define a Range-Doppler Map (RDM) including ground clutter, body and extended rotor returns; initializing at least one search window to exclude ground clutter; comparing the samples within the at least one search window to a constant false-alarm rate (CFAR) threshold to detect potential targets; processing the samples to attempt to extract the body return of the helicopter; modifying the at least one search window to exclude the body return and the ground clutter; comparing the samples within said at least one modified search window to a threshold set above the CFAR threshold using a priori information of a helicopter rotor assembly to identify rotor samples; extracting rotor features including a bandwidth from the rotor samples; and classifying the potential target as a helicopter or other based on at least the bandwidth feature and known bandwidths of the helicopter rotor assembly. 14. The method of claim 13, wherein the threshold is the greater of a predetermined amount above the noise floor of the radar or a predetermined amount below the peak of the body return. 15. The method of claim 14, wherein the amount above the noise floor is a predetermined increment above the CFAR threshold. 16. The method of claim 13, herein extracting rotor features further includes determining an activity measure that estimates a fraction of samples within the bandwidth identified as rotor samples. 17. The method of claim 13, wherein extracting rotor features further includes extracting an angle for each rotor sample and computing a uniformity metric for the angles of the rotor samples. 18. A missile radar system for tracking helicopter, comprising: an aperture for receiving electromagnetic radiation; a receiver configured to convert the electromagnetic radiation into data samples having an amplitude and Doppler shift that define a Doppler map including ground clutter, body and extended rotor returns; a signal processor configured to process the data samples to exclude ground clutter and detect a possible target; and a data processor configured to set a threshold to the greater of a predetermined increment above a constant false-alarm rate (CFAR) threshold or a predetermined amount below the peak of the body return, compare the data samples to the threshold to identify rotor samples within the extended rotor return, extract rotor features from the rotor samples and classify the potential target as a helicopter or other based on the extracted rotor features. 19. The missile radar system of claim 18, wherein the data processor modifies at least one search window in which to identify rotor samples to exclude the body return and the ground clutter. 20. The missile radar system of claim 18, wherein the predetermined increment is set using a priori information of a helicopter rotor assembly. 21. The missile radar system of claim 19, wherein the data processor extracts a bandwidth feature from the rotor samples. 22. The missile radar system of claim 21, wherein the data processor also extracts at least one of an activity measure that estimates a fraction of samples within the bandwidth identified as rotor samples, a uniformity measure of angles associated with each rotor sample, and a shape measure of the extended rotor return. 23. The missile radar system of claim 19, wherein the data processor creates a target report including a classification tag, range, and range-rate of the extended rotor return. 24. A method of missile radar tracking helicopters, comprising: receiving on-board missile radar samples having an amplitude and Doppler shift for multiple range gates that define a Range-Doppler map including ground clutter, body and extended rotor returns; initializing at least one search window to exclude ground clutter across all of the range gates; comparing the samples within the at least one search window across all range gates in the Range-Doppler map to an initial threshold set above the noise floor to detect a potential target at a range gate; modifying the at least one search window for said range gate to exclude ground clutter and body returns and include at least a portion of the extended rotor return; setting a detection threshold above the initial threshold; comparing the samples within said at least one modified search window for said range gate to the detection threshold to identify rotor samples; extracting rotor features from the rotor samples; and classifying the potential target as a helicopter or other based on the extracted rotor features and known attributes of a helicopter rotor assembly. 25. The method of claim 24, wherein the initial threshold varies over time with changes in the noise floor, said detection threshold set at a fixed increment above the initial threshold. 26. The method of claim 24, wherein the initial threshold is a constant false-alarm rate (CFAR threshold) that varies over time maintain an approximately CFAR. 27. The method of claim 24, wherein the detection threshold is set a predetermined amount below the peak of the body return. 28. The method of claim 24, wherein a single said search window is modified to capture a portion of the extended rotor return on the side of the body return opposite the ground clutter. 29. The method of claim 24, wherein the extraction of rotor features from the rotor samples comprises: extracting a bandwidth feature that estimates the bandwidth of the extended rotor return; determining an activity measure that estimates a fraction of samples within the bandwidth identified as rotor samples; and extracting an angle for each rotor sample and computing a uniformity metric for the angles.