Adaptive system and method for radar detection

Communications: directive radio wave systems and devices (e.g. – Return signal controls radar system – Receiver

Reexamination Certificate

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Details

C342S089000, C342S091000, C342S159000, C342S175000, C342S195000

Reexamination Certificate

active

06717545

ABSTRACT:

FIELD OF THE INVENTION
The present invention relates to radar detection, and more particularly, to a system and method for adaptive detection of radar targets.
BACKGROUND OF THE INVENTION
High Frequency Surface Wave Radar (HFSWR) is effective for the continuous detection and tracking of ships, aircraft, icebergs and other surface targets from a shore based location. Accordingly, HFSWR is being used to enhance search and rescue activities as well as to monitor sea state, illegal immigration, drug trafficking, illegal fishing, smuggling and piracy in the Exclusive Economic Zone.
An HFSWR system, installed along a coastal line, comprises a directional transmitting antenna and a receiving antenna array that are directed towards the ocean as well as the hardware and software needed for system operation. The transmitting antenna generates a train of electromagnetic (EM) pulses which illuminate a desired surveillance area. The receiving antenna array should preferably have high and equal gain over the entire surveillance area. Objects in the surveillance area then reflect the EM pulses towards the receiving antenna array which collects radar data. Some of the objects may be elements that must be detected (referred to as “targets”) while the rest of the objects are elements that do not have to be detected (referred to as “clutter”). More sophisticated pulse-coded or frequency-coded EM pulses may be used to combat range-wrap which occurs when a reflected EM pulse (in response to a previously transmitted EM pulse) is received by the receiving antenna array after subsequent EM pulses have been transmitted.
Conventionally, the radar data collected from each antenna element or sensor in the receiving antenna array is then preprocessed by passing the data through a bandpass filter to filter extraneous unwanted signals in the radar data, and then through a heterodyne receiver which demodulates the radar data from the RF band to an IF band where analog to digital conversion occurs. The radar data is then demodulated to the baseband where low-pass filtering and downsampling occurs. The radar data collected by the receiving antenna array is complex (i.e. has real and imaginary components). Accordingly, the downsampled radar data is also complex and each of the signal processing components required to perform the above-mentioned operations are implemented to handle complex data.
The downsampled radar data is then processed by a matched filter that has a transfer function or impulse response that is related to the transmitted EM pulse. The match filtered radar data is then separated into segments for analysis. Each segment is known in the art as a coherent integration time (CIT) or a dwell. The notched filtered radar data in each CIT is range-aligned by noting the time at which each data point was sampled relative to the time that a preceding EM pulse was transmitted. The range-aligned data may then be subjected to a combination of low-pass filtering for further noise reduction and downsampling for more efficient signal processing. The output of this processing is a plurality of time series of range data where each time series is collected for a given range value. The maximum range value for which the plurality of time series is collected depends on the pulse repetition interval used in transmitting the EM pulses (i.e. the frequency at which EM pulses are transmitted).
A target is detected from range, doppler and azimuth information that is generated from the recorded radar data. The range information is used to provide an estimate of the target's distance from the receiving antenna array. The azimuth information is used to provide an estimate of the angle of the target's location with respect to the center of the receiving antenna array and the doppler information is used to provide an estimate of the target's radial velocity by measuring the target's doppler shift. The target's doppler shift is related to the change in frequency content of the EM pulse that is reflected by the target with respect to the original frequency content of that EM pulse.
As mentioned previously, range data is generated by noting the time at which data is sampled relative to the time at which a preceding EM pulse is transmitted. Doppler processing corresponds to the detection of a sinusoidal signal of frequency &Dgr;f at the pulse repetition period (i.e. the time between consecutive transmitted pulses in the coherent pulse train). Accordingly, doppler information is generated for a given range value by subjecting the time series obtained for that range value to comb filter processing, filter bank processing or FFT processing. The azimuth data is conventionally obtained by digital beamforming. More specifically, the radar data at a given range cell and a given doppler cell is weighted by a complex exponential for each antenna element of the receiving antenna array and then summed across all antenna elements. The phase of the complex exponential is related to an azimuth angle, the antenna element spacing and the wavelength of the transmitted EM pulses as is well known to those skilled in the art. Beamforming gives the appearance that the antenna array is tuned to a certain region of the surveillance area defined by the azimuth value used in the complex exponential weights. In this fashion, many beams may be formed to simultaneously cover the entire surveillance area.
To determine a target's range, azimuth and velocity, a detector processes the generated range, azimuth and doppler information for a given CIT. In general, the detector looks for peaks at a given cell (i.e. a data value or pixel) in a two dimensional plot known as a range-doppler plot. Target detection usually comprises comparing the amplitude in a given cell with the average amplitude in neighboring cells. The detected targets are then forwarded to a plot extractor which filters the detected targets to reject all of those detections that do not conform to the range, doppler and azimuth properties that are expected for a true target. These filtered targets are then forwarded to a tracker which associates successive detections of a given target to form a track for the target. In this fashion, the movement of the target may be tracked throughout the surveillance area.
The detection process is hindered by the addition of noise, which includes the clutter previously mentioned, in each cell. This may result in the missed detection of a target or the false detection of noise as a target. The noise is problematic since there will be a varying noise level in different cells as well as for radar data collected in different CITs, in different sea-state conditions, during different times of day and season and at different locations. The major sources of radar noise include self-interference, such as ocean clutter and ionospheric clutter, and external interference. Self-interference results from the operation of the radar while external interference is independent of the operation of the radar.
Ionospheric clutter, one of the most significant causes of interference, includes EM pulses that reflect off of the earth's ionosphere and return directly to the radar (i.e. near vertical incidence clutter), and EM pulses that bounce off of the ionosphere, reflect from the ocean and return to the radar along the reverse path (i.e. sky-wave self-interference or range-wrap clutter). In general, ionospheric clutter accumulates in an annular band spanning several range cells, all azimuth cells and most of the ship doppler band. This narrow band of range cells corresponds to the height or multiple heights of the ionospheric layers relative to the HFSWR installation site. Near vertical incidence ionospheric clutter is also characterized as being very strong, isolated in range and smeared in the doppler dimension over many milli-Hertz. During the night, ionospheric clutter is at its highest level due to the disappearance of the D layer and the merging of the F
1
and F
2
layers. Furthermore, the characteristics of ionospheric clutter vary with season

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