Abstract:
A system and method are disclosed for enhancing the suppression of clutter and target detection in a radar system located on a moving platform. For example, a radar system including an MTI subsystem is located on a moving platform (e.g., ship-borne, airborne or space-based radar system) with a DPCA processing unit located nearer to the front end of the radar receiver, and a STAP processing unit located nearer to the back end. The DPCA processing unit provides gross cancellation and suppression of the received clutter signals, and the STAP processing unit provides fine tuning for the clutter suppression process. In other words, the front end DPCA processing unit removes most of the rapidly varying clutter, which gives the back end STAP processing unit a more benign clutter environment to process. As such, using a DPCA processing unit on a space-based radar platform improves system performance, because the space-based platform is relatively stable and not subject to air turbulence or wave motion. Also, using a DPCA processing unit provides independence from clutter statistics, which is important because relatively little empirical clutter data is available from space-based radar platforms. Using a STAP processing unit for clutter suppression on the space-based radar platform provides fine tuning of the suppression process.

Description:
BACKGROUND OF THE INVENTION  
       [0001]     1. Technical Field  
         [0002]     The present invention relates generally to the field of radar systems, and more particularly, but not exclusively, to a system and method for combining Displaced Phase Center Antenna (DPCA) and Space-Time Adaptive Processing (STAP) techniques in order to enhance clutter suppression and target detection in radar systems located on moving platforms.  
         [0003]     2. Description of Related Art  
         [0004]     Moving Target Indication (MTI) radar systems are used to reject signals received from fixed objects (“clutter”), and enhance the detection of signals received from valid, moving targets. Typically, coherent MTI systems use the Doppler shift effect of moving targets to distinguish them from the fixed objects or clutter. Essentially, clutter is a collective term referring to those objects that are not valid targets and cause unwanted radar reflections to mix with target reflections. Examples of clutter are non-moving objects on land surfaces and/or sea surfaces, such as buildings, trees, ocean waves, clouds, rain, etc. As such, clutter is a form of radar interference that hinders the identification of valid, moving targets.  
         [0005]     Numerous techniques exist for the suppression of clutter by stationary, ground-based radars, where the primary clutter return signals are reflections from fixed objects. However, with moving radar platforms (e.g., ship-based radar, airborne radar, space-based radar), the suppression of clutter is a relatively difficult problem, because the clutter also appears to be moving due to the movement of the radar platform. Consequently, the detection of valid, moving targets within a moving clutter environment is a significant technical problem that exists. Thus, it would be advantageous to have an improved radar system and method that can detect valid targets within a moving clutter environment. The present invention provides such an improved radar system and method.  
       SUMMARY OF THE INVENTION  
       [0006]     The present invention provides a system and method for enhancing the suppression of clutter and target detection in a radar system located on a moving platform. In a preferred embodiment of the invention, a radar system including an MTI subsystem is located on a moving platform (e.g., ship-based, airborne or space-based radar system) with a DPCA processing unit located nearer to the front end of the radar receiver, and a STAP processing unit located nearer to the back end of the onboard processing subsystem. The DPCA processing unit provides gross cancellation and suppression of the received clutter signals, and the STAP processing unit provides fine tuning for the clutter suppression process. In other words, the front end DPCA processing unit removes most of the rapidly varying clutter, which gives the back end STAP processing unit a more benign clutter environment to process. As such, using a DPCA processing unit or stage on a space-based radar platform improves system performance, because the space-based platform is relatively stable and not subject to air turbulence or wave motion. Also, using a DPCA processing unit or stage provides independence from clutter statistics, which is important because relatively little empirical clutter data is available from space-based radar platforms. Using a STAP processing unit or stage for clutter suppression on the space-based radar platform provides fine tuning of the suppression process.  
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0007]     The novel features believed characteristic of the invention are set forth in the appended claims. The invention itself, however, as well as a preferred mode of use, further objectives and advantages thereof, will best be understood by reference to the following detailed description of an illustrative embodiment when read in conjunction with the accompanying drawings, wherein:  
         [0008]      FIG. 1  depicts a pictorial representation of an example of a space-based radar system environment, which can be used to illustrate a preferred embodiment of the present invention;  
         [0009]      FIG. 2  depicts a block diagram of a radar system that can be used to implement a preferred embodiment of the present invention;  
         [0010]      FIG. 3  depicts a block diagram of an MTI processing system that can be used to implement a preferred embodiment of the present invention;  
         [0011]      FIG. 4  depicts a pictorial representation of an example DPCA antenna structure that can be used to implement a preferred embodiment of the present invention;  
         [0012]      FIG. 5  depicts a block diagram of an example ECCM/beam-forming processing function that can be used to implement beam-forming processing unit  306  shown in  FIG. 3 ;  
         [0013]      FIG. 6  depicts a block diagram of an example Doppler filtering processing unit that can be used to implement Doppler processing unit  308  shown in  FIG. 3 ;  
         [0014]      FIG. 7  depicts a block diagram of an example pulse compression processing unit that can be used to implement pulse compression processing unit  310  shown in  FIG. 3 ;  
         [0015]      FIG. 8  depicts a block diagram of an example STAP processing unit that can be used to implement STAP processing unit  312  shown in  FIG. 3 ; and  
         [0016]      FIGS. 9A and 9B  depict related block diagrams of example CFAR processing units that can be used to implement CFAR processing unit  314  shown in  FIG. 3 .  
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT  
       [0017]     Referring now to the figures,  FIG. 1  depicts a pictorial representation of an example of a space-based radar system environment  100 , which can be used to illustrate a preferred embodiment of the present invention. For this exemplary embodiment, an MTI radar system  102  is located on a satellite platform that is in orbit over a portion of the Earth  106 . The satellite platform for radar system  102  can be in a Highly Elliptical Orbit (HEO), a Medium Earth Orbit (MEO), or a Low Earth Orbit (LEO). Also, radar system  102  can be located on a space-based vehicle or station, such as, for example, a space shuttle or similar space vehicle, space-based laboratory, space station, etc. As such, radar system  102  can be located on any appropriate space-based platform. In any event, although a space-based radar system is described with respect to this embodiment, the present invention is not intended to be so limited, and can include radar systems located on other moving platforms as well, such as, for example, airborne or ship-based radar systems.  
         [0018]     Preferably, for this embodiment, radar system  102  includes a phased-array antenna subsystem that can generate an electronically-shaped and electronically-steerable antenna radiation pattern  104 . As shown, radiation pattern  104  depicts a principal lobe of the antenna pattern, which is directed towards a moving target (e.g., aircraft)  112 . Also, certain secondary lobes of antenna pattern  104  are shown directed, for example, towards land-based clutter  108  and sea-based clutter  110 . For this embodiment, the electronically-steerable antenna subsystem can be a phased-array, but it can also include any appropriate antenna structure that can be divided into at least two antenna segments (e.g., typically sharing antenna elements) or one antenna with a plurality of phase centers, which can be used for DPCA processing.  
         [0019]      FIG. 2  depicts a block diagram of a radar system  200  that can be used to implement a preferred embodiment of the present invention. For illustrative purposes only, radar system  200  is described herein for a space-based platform, such as, for example, the satellite platform for radar system  102  shown in  FIG. 1 . However, the present invention is not intended to be so limited, and radar system  200  can also be located on any other suitable airborne, ship-based or space-based platform.  
         [0020]     For this exemplary embodiment, radar system  200  includes an electronically steerable antenna subsystem  202 , with a plurality of antenna elements  204   a - 204   n . For example, antenna subsystem  202  can be a phased array antenna subsystem, or an adaptive array antenna subsystem. Preferably, antenna subsystem  202  is any appropriate antenna structure that can be divided into at least two antenna segments (e.g., typically sharing antenna elements) or one antenna with a plurality of phase centers, which can be used for DPCA processing.  
         [0021]     A beam steering controller  206  is connected to electronically steerable antenna subsystem  202  for directing the radiation pattern of antenna elements  204   a - 204   n . An exciter/transmitter stage  210  is connected to a circulator  208 , which couples the transmission pulses generated by exciter/transmitter stage  210  to antenna subsystem  202  and antenna elements  204   a - 204   n . Circulator  208  is also connected to a receiver stage  212  and couples received signals from antenna elements  204   a - 204   n  through antenna subsystem  202  to receiver stage  212 . Receiver stage  212  is connected to a programmable onboard processing subsystem  214 , so that the raw data in the receiver stage  212  is coupled to programmable onboard processing subsystem  214 .  
         [0022]     Programmable onboard processing subsystem  214  is connected to an onboard processing configurator stage  220  and a communication subsystem  226 . System health and status data, and mode or context control data, are coupled from/to programmable onboard processing subsystem  214  to/from onboard processing configurator stage  220 , respectively. Processed data and target report data are coupled from programmable onboard processing subsystem  214  to communication subsystem  226 , which enables communications between programmable onboard processing subsystem  214  and a ground station (not shown) via an uplink/downlink antenna.  
         [0023]     A real-time waveform designer stage  218  is connected to onboard processing configurator stage  220 , beam steering controller stage  206 , exciter/transmitter stage  210 , receiver stage  212 , and a spacecraft attitude determination and control stage  216 . As such, the real-time waveform designer stage couples waveform design parameters and synchronization signals between stages  220 ,  206 ,  210 ,  212  and  216 . A radar event scheduler/time line generator stage  222  is connected to real-time waveform designer stage  218 , programmable onboard processing subsystem  214 , spacecraft attitude determination and control stage  216 , spacecraft guidance navigation and control stage  224 , and communication subsystem  226 . Thus, the data coupled from control stages  216 ,  224  and subsystems  214  and  226  to real-time waveform designer stage  218  are used to generate timing and synchronization information for the radar system  200  and its space-based platform. Spacecraft attitude and position are coupled to the beam steering controller stage  206  to point the beam at the desired location on the earth. In this manner, the attitude, direction and velocity of the space-based platform can be considered and synchronized with the timing of the radar system&#39;s transmitter and receiver stages.  
         [0024]      FIG. 3  depicts a block diagram of an MTI processing system  300  that can be used to implement a preferred embodiment of the present invention. For this exemplary embodiment, MTI processing system  300  is preferably a coherent MTI processing system, but the present invention is not intended to be so limited and can include a suitable non-coherent processing system as well. As an example, MTI processing system  300  can form part of radar receiver stage  212  shown in  FIG. 2 .  
         [0025]     MTI processing system  300  includes an Analog-to-Digital (A/D) converter unit  302  coupled to the back end of a suitable receiver stage. Thus, for this example, analog signals (e.g., targets, clutter, etc.) input from the receiver&#39;s front end (e.g., coupled from circulator  208  in  FIG. 2 ) are converted to digital signals by A/D converter unit  302 . As such, A/D converter unit  302  quantizes continuous signals input from the receiver&#39;s front end into a series of discrete values for digital processing.  
         [0026]     A/D converter  302  is connected to a DPCA processing unit  304 . Alternatively, for example, DPCA processing unit  304  could be implemented before the A/D converter  302  (e.g., in the antenna manifold). For this exemplary embodiment, the primary purpose of DPCA processing unit  304  is to provide gross cancellation and suppression of received clutter signals. For illustrative purposes, refer now to  FIG. 4  for a description of an example DPCA antenna structure  400  that can be used to implement the present invention. For example, the concept of DPCA antenna structure  400  can be used for implementation of some or all of antenna elements  204   a - 204   n  depicted in  FIG. 2 .  
         [0027]     DPCA antenna structure  400  can be located on a single platform and include a plurality of identical antennas (e.g., two identical antennas having shared antenna elements)  402 ,  404  with separate forward and aft phase centers  406 ,  408 , respectively. Alternatively, DPCA antenna structure  400  can include one antenna with a plurality of phase centers  406 ,  408 . At an appropriate time (e.g., determined by the velocity of the platform for radar system  200  in  FIG. 2  relative to the rotation of the Earth), a transmitter subsystem (e.g., exciter/transmitter  210  in  FIG. 2 ) for radar system  200  transmits a signal from the first antenna  402 . A receiver (e.g., receiver stage  212  in  FIG. 2 ) receives a return signal from antenna  402 . The transmitter subsystem and receiver respectively transmit and receive signals via the second antenna  404 , when the aft phase center  408  has moved into a position that substantially matches the location of the forward phase center  406  when the first transmission and reception occurred. Such movement of DPCA antenna structure  400  is indicated by the arrow  410 .  
         [0028]     As such, in accordance with the present invention, a DPCA processing technique is used to subtract the radar return signals received in response to two transmissions, which cancels most of the rapidly-varying clutter signals received. This technique effectively cancels out the motion of the platform and, therefore, makes the onboard radar sensor appear to be stationary. In other words, subtracting the radar returns from the two transmissions cancels a large part of the stationary clutter (e.g., mountains, buildings, etc.) and ideally leaves only moving targets of interest for further processing. However, although this DPCA processing technique mitigates the clutter returns from stationary objects, some residual clutter can remain (e.g., return signals due to tree branches and leaves blowing in the wind, ocean wave motion, etc.). As a practical matter, performance of the DPCA technique is primarily a function of: (1) how well the two antenna segments are matched; (2) the preciseness of the timing of the transmission of the second pulse; and (3) the location of the aft phase center  408  relative to the location of the forward phase center  406  when the respective transmissions and receptions occur.  
         [0029]     Returning to  FIG. 3 , DPCA processing unit  304  is connected to beam-forming (or beam formation) processing unit  306 . For example, beam-forming processing unit  306  can be implemented using Electronic Counter-Countermeasures (ECCM) beam-forming processing function. As such, the inputs (e.g., coupled to DPCA processing unit  304 ) to beam-forming processing unit  306  can include, for example, 16 channels representing 12 sub-array antenna channels and 4 auxiliary antenna channels (e.g., with 3 time-taps per auxiliary channel). The inputs to beam-forming processing unit  306  can also include, for example, steering vectors for the output beams (e.g., 4 output beams), in a 24 by 4 matrix, with 24 weights per output beam. Thus, beam-forming processing unit  306  can perform processing for each sub-band (e.g., 36 sub-bands), each pulse (e.g., 256 pulses), and each range gate (e.g., 3333 range gates) in this exemplary embodiment.  
         [0030]      FIG. 5  depicts a block diagram of an example ECCM/beam-forming processing function  500  that can be used to implement beam-forming processing unit  306  in  FIG. 3 . For example, beam-forming processing unit  500  can include a 10 msec buffer  502  connected to an input of beam-forming processing unit  306  in  FIG. 3 . A sample matrix  504  is coupled to buffer  502  and can be used for computing adaptive weights by creating a sample matrix (e.g., 24 by 256 matrix) based on pre-transmit collection of data. For example, the sample matrix can be formed by selecting 256 samples for each of the main channels involved (e.g., 12 main channels) and with 3 time-taps per auxiliary channel (e.g., 4 auxiliary channels). Then, a set of adaptive weights can be computed by an adaptive weight computation function or process  506  based on the sample matrix  504  created, and also a 4 by 24 matrix of the steering vectors involved. Thus, as a result, a 4 by 24 matrix of adapted weights can be applied to ECCM/beam-forming processing unit  508  to create (e.g., via a 16-element matrix multiplication) a 4 by 3333 matrix output (e.g., to be coupled from beam-forming processing unit  306  in  FIG. 3  to Doppler processing unit  308 ). As such, beam-forming processing unit  306  can produce a 24-element matrix multiplication for each beam formed, and this process can be performed for each sub-band (e.g., 36), pulse (e.g., 256) and range gate (3333) involved.  
         [0031]     Returning to  FIG. 3 , for this exemplary embodiment, the output of beam-forming processing unit  306  is shown connected to an input of Doppler processing unit  308 , and an output of Doppler processing unit  308  is shown connected to an input of pulse compression processing unit  310 . However, for suitable back end processing, it should be understood that the order of the Doppler and pulse compression processing units can be interchanged. In other words, the output of beam-forming processing unit  306  can be connected to an input of pulse compression processing unit  310 , and an output of pulse compression processing unit  310  can be connected to an input of Doppler processing unit  308 . Essentially, for such an embodiment, Doppler processing unit  308  can perform a Fast-Fourier Transform (FFT) across the radar pulses to convert the input data to the frequency (or Doppler) domain. Pulse compression processing unit  310  can use a matched filter technique that allows a long-pulse radar with moderate output power to appear to be a higher power, short-pulse radar with greatly increased range resolution.  
         [0032]      FIG. 6  depicts a block diagram of an example Doppler filtering processing unit  600  that can be used to implement Doppler processing unit  308  in  FIG. 3 . For example, Doppler filtering processing unit  600  can include a side-lobe weighting vector multiplication processing unit  602  connected to an input of Doppler processing unit  308  in  FIG. 3 . An FFT processing unit  604  is coupled to vector multiplication processing unit  602  and can be used for performing an FFT function on each weighted element received from side-lobe weighting vector multiplication processing unit  602 . For this exemplary embodiment, 256 pulses are coupled to the input of side-lobe weighting vector multiplication processing unit  602 , which performs a 256-element vector multiplication of the input pulses by a set of tapered weights, for example a cosine squared on a pedestal window. As such, a 1 by 256 element vector created by side-lobe weighting vector multiplication processing unit  602  is coupled to the input of FFT processing unit  604 , which performs, for this example, 256-point FFT&#39;s on the weighted samples from side-lobe weighting vector multiplication processing unit  602 . Processing unit  602  creates a 1 by 256 element vector including the 256-point weighted, FFT data. Thus, as a result, using the processing techniques shown in  FIG. 6 , Doppler processing unit  308  in  FIG. 3  can perform Doppler filtering in the pulse/Doppler dimension.  
         [0033]     In this regard, processing units  602  and  604  can perform Doppler filtering and processing for 256 pulses, each range gate (e.g., 71,983 range gates), each beam (e.g., 4 beams), and each sub-band (e.g., 1 sub-band) involved. The output of processing unit  604  (e.g., and Doppler processing unit  308 ) can include, for example, 256 Dopplers for 71,993 range gates, 4 beams, and 1 sub-band. The Doppler processing and filtering can be performed twice on staggered sets of received pulses to generate an output with additional temporal degrees of freedom to support post-Doppler STAP processing. At this point, it should be understood that the present invention is not intended to be limited to the above-described staggered implementation and can also include other implementations such as, for example, beam-staggered STAP implementations and element-staggered implementations.  
         [0034]      FIG. 7  depicts a block diagram of an example pulse compression processing unit  700  that can be used to implement pulse compression processing unit  310  in  FIG. 3 . Notably, as mentioned earlier, pulse compression processing unit  310  may be interchanged with Doppler processing unit  308  in  FIG. 3 . However, for the embodiment(s) shown in  FIGS. 3 and 7 , pulse compression processing unit  700  can include an N-point FFT processing unit  702  connected to an input of pulse compression processing unit  310  in  FIG. 3 , which, for this example, can perform a FFT on each of 89,991 range gates to create an M by N matrix of the FFT data. A vector multiplication processing unit  704  performs a vector multiplication of the M by N matrix of the FFT data with reference data from a 1 by N vector, and creates an M by N matrix including the resulting vector multiplied data.  
         [0035]     Each 1 by N vector from vector multiplication processing unit  704  is applied to the input of an N-point Inverse FFT (IFFT) processing unit  706 , which performs an IFFT function on the data from the M by N matrix. In this manner, for this example, processing units  702 ,  704  and  706  perform a frequency domain convolution on the input pulses (e.g., pulses from 89,991 range gates). For example, this processing can be performed as one large FFT, or more practically, with a number of smaller FFTs using overlap-add or overlap-save techniques. Preferably, the input pulses are uncompressed LFM Chirp waveform length TBD range gates. As such, a linear convolution may be performed on this data in the time domain or the frequency domain. For this example, processing units  702 ,  704  and  706  perform frequency domain convolution (e.g., forward FFT performed by processing unit  702 , element-by-element vector multiplication performed by processing unit  704 , and inverse FFT performed by processing unit  706 ). The output of the overall convolution process is provided in an M by N matrix at the output of N-point IFFT processing unit  706 . As such, an “overlap save” function can be performed if the FFT size either cannot handle all ranges or is inefficient in a single execution. Preferably, for this embodiment, for frequency domain convolution, the uncompressed waveform matched-filter weights and/or the frequency domain representation (transformation) are pre-computed.  
         [0036]     The M by N matrix created by processing unit  706  is applied to a select/truncate processing unit  708 , which performs a truncation. Thus, as a result, the output of select/truncate processing unit  708  can provide 71,993 ranges, and thus pulse compression processing is provided by processing units  702 ,  704 ,  706  and  708  (e.g., by pulse compression processing unit  310  in  FIG. 3 ) for each pulse (e.g., 256 pulses), each beam (e.g., 4 beams), and each sub-band (e.g., 1 sub-band) involved.  
         [0037]     Returning to  FIG. 3 , for this exemplary embodiment, an output of pulse compression unit  310  is connected to an input of STAP processing unit  312 . Thus, in accordance with the present invention, the Doppler processed, pulse-compressed data from processing units  308 ,  310  can be applied to STAP processing unit  312  for fine-tuning of the clutter cancellation process in the example MTI processing stage depicted in  FIG. 3  (e.g., in addition to the gross cancellation process performed by DPCA processing unit  304 ).  
         [0038]     Essentially, in spatial adaptive processing, energy arriving at the antenna elements at different times and phases is used to determine the direction from which unwanted or undesired signals are arriving. The environment is sampled. The sampled data are used to create a training matrix. The training matrix is inverted and solved against desired steering vectors to generate adaptive weights which, when applied to the incoming signals, maximize sensitivity to signals in the desired directions, while nulling out or canceling unwanted or undesired signals. This spatial adaptation technique can be extended to STAP processing by forming a covariance (training) matrix across the input antenna elements (spatial diversity) and the radar pulses (temporal diversity), and then solving for adaptive weights. Adding a temporal aspect allows the STAP technique to be used for clutter cancellation as well as jammer nulling. As such, DPCA processing may be considered a degenerate form of STAP with only two degrees of freedom.  
         [0039]      FIG. 8  depicts a block diagram of an example STAP processing unit  800  that can be used to implement STAP processing unit  312  in  FIG. 3 . For example, STAP processing unit  800  can include a sample matrix  802  (e.g., coupled to an input of STAP processing unit  312  in  FIG. 3 ), which can be used for creating a sample matrix (e.g., a 4 by 500 matrix) from the input samples (e.g., 256 pulses). The input can include, for example, for each of 36 sub-bands, 4 Doppler-staggered beams, 71,993 ranges, and 256 pulses. The resulting sample matrix can be applied to an adaptive weight computation processing unit  804 , which can compute a set of adaptive weights based on the sample matrix  802  created, and also a 3 by 4 matrix of the steering vectors involved (e.g., steering vectors for 3 output beams in a 3 by 4 matrix for 4 weights per output beam formed). Thus, as a result, a 3 by 4 matrix of adapted weights can be applied to STAP beam-forming processing unit  806  to create (e.g., via a 4-element matrix multiplication per output beam) a 3 by 71,993 matrix output (e.g., to be coupled from STAP processing unit  312  in  FIG. 3  to Constant False Alarm Rate (CFAR) processing unit  314 ).  
         [0040]     As such, as a result of the processing performed by processing units  802 ,  804  and  806  in  FIG. 8 , STAP processing unit  312  can produce (e.g., for an input of 256 pulses for 4 input beams, and steering vectors for 3 output beams) an output of 256 Dopplers for 71,993 ranges, and 3 clutter-nulled beams. This STAP beam-forming process can be performed for each sub-band (e.g., 36), each Doppler (e.g., 256), and each range gate (e.g., 71,993) involved.  
         [0041]     Thus, in accordance with the present invention, the STAP beam-forming processing unit  312  can compute the power for each beam, whereby the beam nearest the center of the clutter is used to select 500 samples to form the sample matrix and for computing the adaptive weights (e.g., the selection of the 500 samples can be performed by the Doppler processing unit  308  in  FIG. 3 ). Then, the adaptive weights can be computed based on the sample matrix. The STAP beam-forming processing unit can then multiply a 4-element vector for each beam, sub-band, Doppler and range involved.  
         [0042]     Returning to  FIG. 3 , for this embodiment, an output of STAP processing unit  312  is connected to an input of CFAR processing unit  314 .  FIG. 9A  depicts a block diagram of an example CFAR processing unit  900 A that can be used to implement CFAR processing unit  314  in  FIG. 3 . For example, CFAR processing unit  900 A can include a summing/averaging processing unit  902 A (e.g., coupled to an output of STAP processing unit  312  via a shift register). An output of summing/averaging processing unit  902 A is connected to an input of a local threshold establishment processing unit  904 A. An output of the local threshold establishment processing unit  904 A is connected to an input of a comparison processing unit  906 A.  
         [0043]     In operation, for this exemplary embodiment, the input to the CFAR processing function  900 A is a real sequence formed from the magnitude of the returns for each range cell. For each range cell of interest, a window of N cells is formed around the cell of interest, and the average energy of the returns in the window (excluding the cell of interest and one or more “guard cells” on either side of the cell of interest is computed. This average is used to establish a local threshold which will be used to declare the presence or absence of a target when compared with the magnitude of the return in the cell of interest. The threshold is set to maximize the Probability of Detection (P D ) and minimize the Probability of False Alarm (P FA ), while attempting to avoid the making of a decisional error, such as, for example, declaring no target when a target is actually present, or declaring a target when none is present. The “window” can be slid from cell to cell, or through the entire sequence of range cells. However, care must be taken when dealing with range cells on the extremes, because the window from which the samples are taken is not symmetric.  
         [0044]     As such, a number of techniques may be used to compute the average and use the threshold. For example, the average can be computed from scratch each time. Also, a more computationally efficient approach realizes that, for the next movement of the window, most of the “sum” already exists. Adding the contributions from the leading edge of the window and the left-most guard cell from the previous window, and subtracting the contributions from the trailing edge of the window and the right-most guard cell from the previous window, is all that is needed to create the new sum. It is also possible to perform this summation as a sliding matrix multiplication of the input cells with a . . . 111110000011111 . . . mask.  
         [0045]      FIG. 9B  depicts a block diagram of a second example CFAR processing unit  900 B that can be used to implement CFAR processing unit  314  in  FIG. 3 . As such, CFAR processing unit  900 B is a 2-dimensional (range and Doppler) CFAR, while CFAR processing unit  900 A in  FIG. 9A  is a 1-dimensional (range) CFAR. For this example, CFAR processing unit  900 B can include an extraction processing unit  902 B for extracting a cell of interest from the input, and zeroing out the cell and guard cells. An output of extraction processing unit  902 B is connected to an input of a summing/averaging processing unit  904 B. An output of summing/averaging processing unit  904 B is connected to an input of a local threshold establishment processing unit  906 B. An output of the local threshold establishment processing unit  906 B is connected to an input of a comparison processing unit  908 B.  
         [0046]     In accordance with the present invention, the output of CFAR processing unit  900 A in  FIG. 9A  or  900 B in  FIG. 9B  is detected video/target information with enhanced clutter suppression due to the use of DPCA and STAP processing techniques. This video/target information can be transferred to the ground via the communication subsystem unit  226  and coupled to a video/target display for use by an operator (e.g. from CFAR processing unit  314  in  FIG. 3  at the back end of the programmable onboard processing subsystem  214  shown in  FIG. 2 ).  
         [0047]     In operation, CFAR processing unit  900 B can perform a 2-dimensional CFAR function. A sliding window cell-averaging algorithm can be used for sizing purposes. A primary difference between the 2-dimensional CFAR in  FIG. 9B  and the 1-dimensional CFAR in  FIG. 9A  is that the local averaging is accomplished in the 2-dimensional CFAR  900 B in  FIG. 9B  using the Doppler cell of interest and adjacent Doppler cells above and below the Doppler cell of interest. However, no guard banding is used in the Doppler dimension (i.e., all range gates in the adjacent Doppler cells are included in the average and subsequent threshold determinations).  
         [0048]     It is important to note that while the present invention has been described in the context of a fully functioning radar processing system, those of ordinary skill in the art will appreciate that the processes of the present invention are capable of being distributed in the form of a computer readable medium of instructions and a variety of forms and that the present invention applies equally regardless of the particular type of signal bearing media actually used to carry out the distribution. Examples of computer readable media include recordable-type media, such as a floppy disk, a hard disk drive, a RAM, CD-ROMs, DVD-ROMs, and transmission-type media, such as digital and analog communications links, wired or wireless communications links using transmission forms, such as, for example, radio frequency and light wave transmissions. The computer readable media may take the form of coded formats that are decoded for actual use in a particular radar processing system.  
         [0049]     The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiment was chosen and described in order to best explain the principles of the invention, the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.