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  • Jay June 2015

Passive RADAR

edited May 2015 in RADAR Discussions
Passive RADAR discussion: (definition) detect and track objects by processing reflections from non-cooperative sources of illumination (transmitters) in the local environment, such as commercial broadcast and communications signals. Passive RADAR may mistakenly be referred to as Bistatic RADAR and may referred to many different ways (Passive Bistatic RADAR 'PBR', Passive Coherent Location 'PCL', etc.), here, this is not the case. Bistatic RADAR utilizes a Transmitter which is in control and cooperates with the receiver just like Monostatic RADAR, the transmitter and receiver are just in different locations. With Passive RADAR, the Transmitter is only one of convenience, and is not cooperating with the receiver(s). Being that powerful FM Standard Broadcast Radio Transmitters are in or near all major cities on Earth, the opportunity to take advantage of this free resource has been overlooked, until now.


  • JayJay
    edited May 2015
    Geometry of Meteor Region in relation to Passive RADAR antennae. 

    The volume of Space able to be monitored by Passive RADAR is immense. While not effective for Over-the-Horizon detection, movement in Near Earth Orbit as far away as 300 miles is possible. Aircraft, Meteors, and Satellites directly overhead and in line of site are easily detected. Detectable objects of Interest:
    Satellites, Asteroids, The Moon, Meteors entering the upper atmosphere, Aircraft including Drones and Stealth vehicles, Missiles/Rockets, flocks of Birds, Trains, Ships, Automobiles, and Storms.RADAR Geometry
  • JayJay
    edited May 2015
    Block Diagram of a proposed Passive RADAR Receiver for monitoring reflections from FM Standard Broadcast Radio Transmitters utilizing 2 modified SoftRock-like SDRs.

    For Passive RADAR, Dynamic Range is far more important than wide Bandwidth. Broadband transmissions provide higher resolution in Range determination, however, reflections of the transmitter from distant Meteors are buried in interference and noise, requiring deep bit depth to correlate the smallest returns providing high resolution Doppler discrimination (Velocity).

    2 "SoftRock Ensemble" Receivers can be altered to accommodate dual antennae, required for a minimum RADAR Receiver. There is a convenient Audio Interface that allows 4 channel, 192k/24 bit depth on each channel, way more dynamic range than is needed, but more is better in this case. With 4 input channels, 2 sets of I/Q signals can be directly converted to provide high resolution signals from 2 Antennae at 192 kHz bandwidth on each. This will allow Doppler/Ranging of one transmitter, hopefully in real time.
  • JayJay
    edited May 2015

    Passive RADAR; more difficult than folding Bowling Balls, here is knowing why.

    Cross – Correlation is the signal process needed to extract echoes from Passive RADAR reception. Conceptually it removes the greater signal from the lesser signal leaving behind the artifacts the greater signal impressed on the environment, called the impulse response. Much like filtering out the loud sound of a Band and hearing only the reflections from nearby objects in an outdoor concert. In this case the Sound of the Band is the RF from a Standard Broadcast FM Radio Station Transmitter reflecting off objects moving in the nearby Space around the concert goer (Receiver). The reflections off the Ground must be considered part of the performance, but in this case it is not moving so reflection off the Ground and other stationary objects called Clutter and Multipath may be effectively removed. Static reflections change very slowly with periods of change of minutes to days, much more slowly than moving objects; changes in the miliseconds.

    Cross-correlation and convolution are similar, to perform convolution on two signals with the FFT…

    1. In 2 buffers (matrix), one for each signal, (a,b), zero-pad each matrix (add zeros to the end, so at least half of each stream is "blank") =( a_and_zeros, b_and_zeros)

    2. perform the FFT of both signals = fft(a_and_zeros), fft(b_and_zeros)

    3. multiply the 2 resultant FFTs (element-wise multiplication) = fft(a_and_zeros) * fft(b_and_zeros)

    4. perform the Inverse FFT on the product = ifft(fft(a_and_zeros) * fft(b_and_zeros))

    The convolution of (a, b) = ifft(fft(a_and_zeros) * fft(b_and_zeros))

    Zero-padding is required because the FFT method is actually circular cross-correlation; the signal wraps around at the ends returning to the beginning. Each Matrix must be Buffered by adding enough zeros to negate the overlap, this simulates a signal that starts at zero and goes to infinity, called a “Window”.

    For cross-correlation instead of convolution, either time-reverse one of the signals before performing the FFT on it, or take the complex conjugate of one of the signals after the FFT:

    corr(a, b) = ifft(fft(a_and_zeros) * fft(b_and_zeros[reversed]))

    corr(a, b) = ifft(fft(a_and_zeros) * conj(fft(b_and_zeros)))

    whichever is easier.

    To get your brain around this…

    Imagine 2 Carousels are created every second, each with one million horses on them (or the number of horses appropriate for the sample temporal window of interest). The height of each horse is the magnitude of the signal, in time. Every second, convert the previous 2 sets of million magnitudes to the frequency Domain (time to frequency performed by the FFT) and put these frequency magnitudes in a set of bins. Multiply these 2 sets of million magnitudes and store the product in a new set of bins. Convert this product back to the Time Domain (the Inverse FFT) to create the Correlation Matrix.

    To top this off, if the Correlation Matrix is to be displayed in real time, these complex Functions must be performed in real time to be observed in real time, then converted in such a way to provide a Graphic User Interface (GUI). It is also required to perform Detection of False Alarms, a basic function in RADAR, plus filtering the stream of signal DATA based on Velocity and Range to eliminate unwanted clutter and non-Newtonian movement in the display. In addition, reports of activity must be calculated and stored in such a way that the report is usable and accessible in the immediate and long-term future.

    This is why surveillance RADAR costs Millions of Dollars,
    usually a concoction of custom very high speed processors, software, and esoteric Hardware.

    Intertwine plus Intermingle = Intertwingle.

  • JayJay
    edited May 2015
    My name is Jay Salsburg. I live in Shreveport, Louisiana, USA. 

    I have embarked on a project to create a low cost Passive RADAR Receiver set, now ongoing for many years. Originally, what peeked my interest in Meteor RADAR was my success detecting Meteor activity with the NAVSPASUR Space RADAR in Texas about 300 miles from my location.

    Unfortunately, after 50 years in operation, the NAVSPASUR Million-Watt Transmitter has been permanently shut down. Since then, I have been researching methods to detect Meteors using Passive RADAR. After many months of intense investigation with Tuner Dongles, I have concluded Tuner Dongles are not suited to this task of Passive RADAR.

    A PC using TV Tuner Dongles will almost never perform well at this task, remaining only a curiosity because: 

    First; the Dongle's 8-bit dynamic range limitation

    Second; Poor signal image rejection

    Third; Lack of a way to filter the Antenna Amplifier input and output inside the tuner

    Forth; the USB output is separate from other Dongle USB DATA streams making DATA fusion imprecise. 

    Standard Broadcast FM Radio Stations are in or near every major City on Earth. Using these Transmitters as illumination sources, Passive RADAR provides the distinct advantage of determining Doppler Velocity, and Range or Distance. For instance, Meteor Counting does not require Targeting, thereby reducing complexity and cost. However, Meteor Counting remains very computation intensive, and requires special Hardware and Antennae. 

    The target research is to create a Passive RADAR System as inexpensively as possible. Sure, throwing money at the task will produce success, but high cost and complexity excludes most Amateur Observers. Low cost translates to increased market size, and early adoption.

    Passive RADAR remains the domain of well-funded Military Contractors. As time goes on, however, this technology will become accessible to millions of Amateur enthusiast. 
  • JayJay
    edited May 2015
    Rules of Passive RADAR (Ongoing)

    1. Minimum configuration; One transmitter, 2 receivers, 2 antennae.
    2. The minimum of 2 receivers are phase-locked to the same timebase (clock/crystal).
    3. 2 antenna, one on each receiver some form of isolation from each other to reduce swamping of reflected signals.
    4. Range resolution is determined by the bandwidth of the transmitter energy or the speed of light divided by this bandwidth.
    5. Targets must have a simultaneous line of sight from the transmitter antenna and the receiver antenna.
    6. The transmitter and the receiver are at separate locations preferably near the horizon from each other.
    7. These locations typically do not change with time (stationary). 
    8. These minimum 2 sites are separated by a baseline whose length is usually comparable with the ranges to the targets of interest. 
    9. As in monostatic radars, the range of a target can be determined by a time delay measurement, provided that the length and orientation of the baseline are known. In Passive RADAR, the time is that for propagation from transmitter to target to receiver and its value defines a Prolate Spheroid with the transmitter and receiver sites as foci. Only with multiple transmitters and sets of receivers the (3 dimensional) location of the target on the surface of this spheroid may be determined by the azimuth and elevation angles of the transmitters antennas in relation to the receiving antennas.
    10. The algorithm of interest for subtracting the Illumination energy from the Reflected energy is the Two Dimensional Cross Correlation Function (2D-CCF). Targets are detected on the cross-correlation surface by applying an adaptive threshold, and declaring all returns above this surface to be targets. 
    11. A standard cell-averaging constant false alarm rate (CFAR) algorithm is typically used.
    12. Passive RADAR uses Staring, not temporal and directional Pulsing like Weather or Navigation RADAR, meaning it is always looking for a “Hit” within its range.
    13. Wide Bandwidth reveals greater Range detail and resolution.
    14. Theoretical distance resolution = c (speed of light) / Bandwidth (actual resolution is never this accurate) times 2 (going and coming)
    15. Broadcast FM 200 KHz, Digital HD FM 400 KHz, Digital TV 6 MHz.
    16. FM resolution = (300,000,000/200,000)*2 = 3000 meters 
    17. Digital HD FM = (300,000,000/400,000)*2 = 1500 meters
    18. Digital TV = (300,000,000/6,000,000)*2 = 100 meters
    19. FM 100 MHz, Digital TV 470 to 770 MHz
    20. Analog FM is usable but exhibits undesirable short term modulation, high modulation index punctuated with periods of near zero modulation.
    21. Digital HD FM is more desirable signal: Continuous high density modulation, 400 KHz bandwidth.
    22. In addition to determining Range; to determine Angle of Arrival (Targeting), 5 sets of Receivers/Antennae are necessary; 7 sets are much better (Tracking).
    23. Signals of interest are always moving (Doppler filter).
    24. Static signals (Clutter) are ignored.
    25. Slow-moving Signals (birds, rain, snow, ground vehicles, perpendicular movement) are ignored unless these slow movers are of interest.
    26. Range, Velocity, and Target Information is distorted in Space-Time (Prolate Spheroidal) due to separation of Transmitter and Receiver.
  • JayJay
    edited May 2015

    My efforts with Passive RADAR are to create a receiver/software/computer set allowing the user to monitor local activity in the space nearly overhead; above the line between a local transmitter and the user’s receiver set. 

    Over the horizon Forward Scatter reception is effective for the enthusiast, but it suffers from lack of the ability to automatically monitor and record unattended, the activity in the user’s nearby space, the scatter is typically by default a great distance away, only in a narrow direction, and is troubled by interference from many unwanted reflections like Aircraft.

    Passive RADAR offers something Forward Scatter RADAR does not; reliable nearby Range and Velocity measurement. This allows filtering of unwanted strong reflections from nearby movement like Aircraft which has been the bane of Forward Scatter RADAR monitoring from its inception, unless your intent is to monitor nearby Aircraft. This is why it is so difficult to use the computer for instance to count Meteors or alarm on movement of interest with this technique; Forward Scatter RADAR is dimensionless. The now-retired NAVSPASUR transmissions were a special case. The NAVSPASUR transmitter was very powerful, no interference, focused into a fan beam or Fence, and carrier wave with no modulation. There are few if any transmitters of convenience left on Earth with these special and expensive characteristics.

    Passive RADAR promises to utilize Transmitters of convenience in and around all major cities. This provides the opportunity for a large percentage of the total Human population numbering in the tens of millions able to take advantage of this untapped resource.
  • JayJay
    edited May 2015
    Books and Papers of interest...

    Principles of Modern Radar, Vol. II: Advanced Techniques,
    William L. Melvin, James A. Scheer, Georgia Institute of Technology
    ISBN 978-1-891121-53-1 (hardback)
    ISBN 978-1-61353-024-5 (PDF)

    The Scientist and Engineer's Guide to Digital Signal Processing, Second Edition,
    Steven W. Smith,
    ISBN 0-9660176-7-6 hardcover
    ISBN 0-9660176-4-1 paperback
    ISBN 0-9660176-6-8 electronic
    LCCN 97-80293

    Advanced radar techniques and systems,
    Gaspare Galati,
    ISBN 0 86341 172 X

    FM radio based bistatic radar,
    P.E. Howland, D. Maksimiuk and G. Reitsma,
    IEE Proceedings online no. 20045077
    doi: 10.1049/ip-rsn:20045077

    Radar Systems Analysis and Design Using MATLAB,
    Bassem R. Mahafza, Ph.D.,
    ISBN 1-58488-182-8

    Modern Radar Systems,
    Hamish Meikie,
    ISBN 1-58053-294-2

  • JayJay
    edited May 2015

    Passive RADAR has received renewed interest for surveillance purposes. 

    It allows for target detection and localization with many advantages such as low cost, covert operation, low vulnerability to electronic countermeasure, and reduced electromagnetic pollution. Passive RADAR exploits an existing transmitter as an illuminator of opportunity. A receiving system is appropriately designed to receive the echoes reflected from targets and sited to provide coverage of a specific area.

    Broadcast transmitters of commercial radio stations in the frequency modulation (FM) radio band 88–108 MHz are especially attractive for their generally high level of transmitted power, for their wide coverage, and for the limited cost of the required receivers.

    Digital video broadcasting-terrestrial (DVB-T) and digital audio broadcasting (DAB) transmitters are replacing their analog counterparts in a large portion of the world and are characterized by wide coverage and wider bandwidth and thus better resolution. In addition, they benefit from the typical characteristics of their digital orthogonal frequency-division multiplexing (OFDM) modulation, together with their known coding scheme.

    The low power signal reflected from the target is collected by the main Passive RADAR receiver (typically known as the surveillance channel) using a directed antenna pointing toward the surveillance area. Since the transmitted signal is not known at the receiver, an auxiliary Passive RADAR receiver (typically known as the reference channel) is usually connected to an additional directed antenna pointing toward the transmitter.

    The signal collected at the reference channel is first used to remove undesired contributions that have been received, along with the moving target echo, on the surveillance channel. Such disturbances result from the fraction of the direct signal coming from the transmitter and received by the sidelobes or backlobes of the surveillance antenna, as well as the strong clutter/multipath echoes. This problem can have major relevance when the direct signal contribution is strong and affected by multiple reflections on the surface or on discrete scatterers. Various approaches have been proposed to cope with this problem typically some kind of physical barrier or fence is erected to reduce the unwanted signal. After the cancellation stage, the detection process is based on the evaluation of the bistatic two-dimensional (range-velocity) cross-correlation function (2D-CCF) between the surveillance and the reference signal. A constant false alarm rate (CFAR) threshold can be then applied on the obtained map to automatically detect the potential targets according to a specific CFAR detection scheme.

  • JayJay
    edited May 2015


    While it is not especially challenging to evaluate the 2D-CCF from a signal processing point of view, it can be in terms of the computational load that it requires for real-time application. The long integration times (order of magnitude of seconds) required to extract the low-level target signal from the disturbance implies a large number of complex multiplications to be performed. Moreover, long coherent integration times of this type provide a high Doppler frequency resolution; thus, high number of Doppler filters is required. Finally, the computational load is also proportional to the bandwidth of the specific waveform of opportunity used in the system because the bandwidth sets the minimum required sampling frequency. Therefore, evaluation of the 2D-CCF for wide bandwidth waveforms (like WiFi and LTE) has a very high computational cost this does not apply so much to MCR (METEOR-COUNTING RADAR). By observing that the expected target echo belongs to a limited area of the bistatic range-Doppler plane, the computational load can be lowered by appropriately selecting the filter implementation approach that best matches the region of the bistatic range-Doppler plane of interest and by considering approximate filtering schemes. 

    The disturbance cancellation technique is of particular importance when it is difficult to avoid a significant signal power arriving directly from the transmitter of opportunity into the sidelobes of the surveillance antenna. For a long range target, the power ratio of direct signal received through the sidelobes and desired signal can get close to 100 dB so that the cancellation technique has a significant challenge. This is especially the case of Passive RADAR operating at relatively low frequency, where it is very difficult to reduce the receiving antenna sidelobes to a very low level. This is clearly experienced with FM-based Passive RADAR

  • JayJay
    edited May 2015

    2D-CCF and interference cancellation.

    While the basic detection scheme is fully defined by the previously mentioned described cancellation and integration techniques, the effectiveness of the Passive Radar operation can be largely enhanced by considering an advanced Passive Radar processing scheme.

    First we notice that both 2D-CCF and interference cancellation assume a perfect knowledge of the transmitted waveform. In contrast, in practice the transmitted waveform is estimated by means of the reference channel, and that is affected by all transmitter, propagation, and receiver modifications. Therefore, it might be necessary to perform some transmitter-specific conditioning of the received signal before cancellation and 2D-CCF evaluation, and this depends on the specific waveform of opportunity exploited. These may include high-quality analog bandpass filtering, channel equalization, removal of unwanted structures in digital signals, or complete reconstruction from the received digital signal. Such conditioning approaches are mainly intended for the reference signal to improve:

    • Its quality (with a benefit for the cancellation step). This aspect is addressed in the subsequent sectio on Signal Processing Techniques that analyzes the effect of multipath contributions in the reference signal and shows that these contributions represent the main cause of degradation of the reference signal quality. Proper techniques are introduced to remove such undesired contributions from the reference signal for Passive Radar systems exploiting both analog and digital transmissions: in the latter case, the possibility to demodulate them and reconstruct their multipath-free version.
    • The resulting ambiguity function (AF). Passive Radar operation inherently implies that the transmitted waveform is not within the control of the radar designer applies to MCR. This contrasts to the usual case of conventional radar systems, where the transmitted waveform is carefully designed to provide an AF with appropriate properties (e.g., narrow peak in both range and Doppler and low sidelobes).  Digital transmissions, are usually characterized by a number of undesired peaks or high sidelobes in the corresponding 2D-CCF and have a severe masking effect on small targets. Therefore, proper techniques are introduced to cope with this undesired effect in Passive Radar systems based on digital transmissions exploiting different modulation schemes.


  • JayJay
    edited May 2015
    More Rules
    1. Passive RADAR exploits existing illuminators of opportunity which results in the possibility of low cost surveillance, covert operation, and reduced electromagnetic pollution.
    2. 2D-CCF represents costly processing steps in terms of computational burden due to long coherent integration times. For real time operation, cost-effective solutions can be adopted based on both optimum and sub-optimum techniques.
    3. Disturbance cancellation is a required step in the typical Passive RADAR processing scheme since it allows the removal of undesired contributions received on the surveillance channel along with the moving target echo (i.e. direct signal from the transmitter and strong clutter/multipath echoes).
    4. The reference signal is usually assumed to be a high-quality copy of the transmitted signal. In practice, some transmitter-specific conditioning of the reference signal may be performed to improve its quality and hence the Passive RADAR performance.
    5. Passive RADAR operation inherently implies that the transmitted waveform is not within the control of the radar designer. However, in specific cases, proper filters can be used to control the sidelobes of the resulting ambiguity function (AF).
  • JayJay
    edited May 2015


    The evaluation of the bistatic range-velocity 2D-CCF is the key step in the Passive RADAR processing chain. It corresponds to the implementation of a bank of matched filters, each one tuned to a specific target bistatic velocity. Typically the values of velocity are chosen with a separation approximately equal to the bistatic velocity resolution. Therefore, the set of filters covers all the possible target velocities. The filter where the target is detected provides the estimates of the bistatic Doppler shift of each target echo. Similarly, the estimate of the bistatic range is given by the sample along range where it is detected. Assuming that the signal sref(t) collected at the reference antenna is a perfect copy (or at least good enough) of the transmitted signal, the 2D-CCF for a Passive RADAR is evaluated as further discussion (of the Mathematics) is beyond the scope of this FORUM.

    The evaluation of the 2D-CCF for a Passive RADAR represents one of the most costly operations in terms of computational burden. In fact, the exploited waveform of opportunity typically has a low power level for radar purposes, so a very long integration time is usually required to obtain an acceptable signal-to-noise ratio (SNR). Moreover, large 2-D maps might be required depending on the desired surveillance region extent in both range and Doppler dimensions. This implies that a huge amount of data has to be managed and a large number of complex operations has to be performed that might require very fast hardware for real-time processing.


    As is intrinsic in the passive radar concept that involves parasitically exploiting an existing transmitter of opportunity, the characteristics of the transmitted waveform are not under the control of the radar designer and are not tailored for radar application. Because they are used for transmission of information, the waveforms of opportunity have an intrinsic random behavior. This implies that very often their ambiguity function (AF) have time-varying sidelobe structures along both bistatic range and Doppler. Moreover, these sidelobes exist at a level not greatly lower than the peak. This can lead to the following:

    1. Strong clutter echoes masking targets with high Doppler frequencies
    2. A small fraction of the direct signal being received via the sidelobe/backlobe of the surveillance antenna (still significantly larger than the clutter echo) that masks target echo signals
    3. Strong target echoes masking other echoes from other targets of a lower level, even in the presence of large range-Doppler separations

     In addition to using carefully designed waveforms, in active radar systems these problems are typically addressed either by applying tapering to the received signal to lower the sidelobes or by using moving target indication (MTI) canceller filters to remove the strong stationary clutter echoes. Unfortunately, neither of these can be directly applied to passive radar.

    The principle of operation of the adaptive cancellation filter is that, by summing up a number of appropriately delayed and weighted replicas of the transmitted waveform, an estimate of the undesired interference signal is obtained. This estimate is then subtracted from the received signal to remove the interference component.

    To follow this approach, the transmitted waveform must be known. The reference signal is thus assumed to be a good replica of the transmitted signal. Specifically, since the direct signal is received by the main lobe of the reference antenna, it is assumed that target and clutter echoes (received from the sidelobes) are negligible. Furthermore, for the sake of simplicity, it is assumed that the reference signal is free of multipath. Under these assumptions, by appropriately filtering the reference signal (a FIR filter with a number of taps emulates the multiple reflections from stationary objects) an adaptive estimate of the undesired contributions in the surveillance signal is obtained. This estimate will then be subtracted from the original signal, leaving an estimate only of the desired target echoes.


    The cancellation and the 2D-CCF evaluation algorithms presented in the previous sections assume the availability of a clean reference signal that corresponds to a high quality copy of the transmitted signal. Therefore, it might be necessary to perform some transmitter-specific conditioning of the signal that depends on the exploited waveform of opportunity—for example, high-quality analog BP filtering, channel equalization, removal of unwanted structures in digital signals, and complete reconstruction from the received digital signal—before cancellation and 2D-CCF evaluation. Such conditioning approaches are mainly intended for the reference signal aiming at improving its quality (with a benefit for the cancellation step) and the resulting AF (with reduced masking effect for small targets).

    Except for the presence of thermal noise in the reference channel, the main degradation to the signal quality is typically related to the presence of multipath. Whereas the basic processing techniques were introduced with the assumption that no multipath is present, it is easy to imagine that the presence of multipath in the reference signal would yield significant performance degradation. For this reason, different techniques have been proposed to remove such undesired contributions from the reference signal. Obviously, these techniques are waveform dependent and might be based on previous literature for both analog and digital transmissions on channel equalization.

  • JayJay
    edited May 2015

    Constant Modulus Algorithm for Reference Signal Cleaning Using Analog Modulation

    To investigate the performance degradation of a Passive RADAR exploiting a reference signal affected by multipath, the following model is adopted for complex envelope of the signal collected at the reference antenna: further discussion (of the Mathematics) is beyond the scope of this document.

    Thus, proper techniques should be applied to remove the multipath contribution on the reference signal, yielding a pure signal to be used for disturbance cancellation and cross-correlation with the surveillance signal.

    Specifically, assuming that the PBR is based on FM radio broadcast transmissions, the well-known constant modulus algorithm (CMA) can be exploited to obtain a blind adaptive equalization of the reference signal. This kind of approach is not limited to our study case, based on FM radio broadcast, but also applies to many of the signals of opportunity available from both analog and digital broadcast transmission systems. Applying CMA to Passive RADAR is considered for an FM-based Passive RADAR , where only a basic temporal version of the algorithm is applied. ...Consider the possibility of using a small antenna array for the reception of the reference signal from the transmitter of opportunity, and two additional versions of the algorithm are used for Passive RADAR application along the line suggested: the space constant modulus algorithm CMA (S-CMA) that operates on the signal samples collected at the different elements of the array; and the space-time constant modulus algorithm CMA (ST-CMA) that operates on the delayed samples of the signals collected at the multiple channels.

    The CMA tries to suppress the additive interference at the input signal by constraining its output to be a constant modulus signal, accomplished by minimizing the cost function further discussion (of the Mathematics) is beyond the scope of this document.

  • JayJay
    edited May 2015

    Reference Signal Reconstruction for Digital Transmissions

    When digital transmissions are exploited by a Passive RADAR, the multipath removal from the reference signal can be performed by demodulating the signal received at the reference antenna. A quite good copy of the transmitted signal can then be obtained by remodulating the resulting symbol sequence according to the transmission standard.

  • JayJay
    edited June 2015

    Here is a synopsis of the Physical Layer. (Part 1 of 3)  (incomplete)

    Passive RADAR

    · A subclass of Bistatic RADAR.

    · Uses someone else's Transmitter (can be 100,000 Watts or more), usually Broadcast FM and TV.

    · Another version may use Cellular Telephone Transmitters, but is limited to short Range.

    · Uses multiple (minimum 2) Coherent Receivers each with its own specialized Antenna or Antenna Array.

    · An alternative is other RADAR Transmitters (GHz).

    · Options; may utilize more than one Transmitter and multiple Receiver locations (provides Targeting Vectors for Tracking).

    · Passive RADAR uses Staring (like why are you staring at me), not temporal and directional Pulsing like Weather or Navigation RADAR, meaning it is always looking for a “Hit” within its range.

    · Receivers must be temporally Synchronized, else problems arise, some insurmountable.

    · Digitize signals from Reference/Surveillance Antennae.

    · Perform Signal Processing on signals (difficult, time-consuming math).

    · Real-Time Signal Intelligence; very costly.

    · Outcome of Signal Processing; at minimum, Range and Velocity, perhaps Targeting with multiple Receivers.

    · Range, Velocity, and Target Information is distorted in Space-Time due to separation of Transmitter and Receiver.

  •  Here is a synopsis of the Physical Layer. (Part 2 of 3)  (incomplete)

    Passive RADAR

    Transmitter Attributes (Standard Broadcast FM and TV)

    · No control of signal but understand its characteristics.

    · Wide Bandwidth reveals greater Range detail and resolution.

    · Theoretical distance resolution = c (speed of light) / Bandwidth (actual resolution is never this accurate)

    · Broadcast FM 200 KHz, Digital HD FM 400 KHz, Digital TV 6 MHz.

    · FM resolution = 300,000,000/200,000 = 1500 meters

    · Digital HD FM = 300,000,000/400,000 = 750 meters

    · Digital TV = 300,000,000/6,000,000 = 50 meters

    · FM 100 MHz, Digital TV 470 to 770 MHz

    · Analog FM is usable but exhibits undesirable short term modulation, high modulation index punctuated with periods of zero modulation.

    · Digital HD FM is more desirable signal: Continuous high density modulation, 400 KHz bandwidth.

    · Analog FM yields 3 km maximum resolution; may reveal better resolution with extended signal post processing.

  •  Here is a synopsis of the Physical Layer. (Part 3 of 3)  (incomplete)

    Passive RADAR

    Signal Processing Attributes

    · In addition to determining Range; to determine Angle of Arrival (Targeting), 5 sets of Receivers/Antennae are necessary; 7 sets are much better (Tracking).

    · Signals of interest are always moving (Doppler filter).

    · Static signals (Clutter) are ignored.

    · Slow-moving Signals (birds, rain, snow, ground vehicles, perpendicular movement) are ignored.

  • JayJay
    edited June 2015
    In the USA, most major cities have at least one Station broadcasting Digital HD FM. This source of constant modulation energy seems to be overlooked for Passive RADAR. These Digital transmissions seem to be ideal for overcoming Range Ambiguity difficulties. Each transmitter is broadcasting two, 100 KHz wide Digital signals whose amplitude does not vary and are full of multiple constant carriers and very dense modulation. Listening to them with an “Analog” superhet receiver they sound like white noise. Examining them closely with FFT, they appear well suited for Ranging, perhaps with an accuracy of 1500 meters. Notice on the right side of the Spectral plot, this FM Station's modulation has returned to near zero. The three large peaks are pilot subcarriers. This lack of modulation is what causes characteristic unwanted flat autocorrelation. If there is nothing to correlate it is just like multiplying by zero. The range appears to be everywhere and nowhere at once. The consistent high density modulation of the Digital FM transmission guarantees Range determination errors fall within usable products. Notice on the left, the typical band of this station's highly dense Digital transmission, which could be used as a second source of Passive RADAR.
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