Dynamic Scan Scheduler for ANT-Based Scan Scheduling

1. ANT-Based Dynamic Scan SchedulingANTSNortheastern/Sanders

2. Outline • The scheduling problem • Use Case: Fixed Scan Scheduler • From FSS to Dynamic Schan Sched. (DSS) • Dynamic Scheduling via negotiation • Plans

3. Scenario A B C

4. Scenario - discussion Consider a threat pulsed radar in surveillance mode with pulse-repetition interval  in the order of 1 msec (200-km unambiguous range). (The interval  can be as small as 10 s.) The principal lobe of its antenna pattern is a fan beam in elevation with a 1-deg azimuth beamwidth. The beam scans 360 deg in 3 sec. Therefore, its illumination time at a point fixed in the far field will be 8 msec. (3sec/360) The desired EW-receiver revisit time, , is therefore 8 msec. This is the largest time interval that guarantees that the illumination of the threat can be captured by the EW receiver (the receiver’s dwell time and the emitter’s illumination time intervals will overlap). At least three pulses must be detected in order for the EW receiver to correctly identify the emitter. (Parameter M on next page: M >=3.) Therefore, the EW-receiver dwell  cannot be less than 3 msec. This assumes that the Pulse Repetition Interval (PRI) is 1msec. If PRI is smaller than 1msec, then the dwell time can be shorter.

5. Emitter Parameters Emitter Signal Time Pulsewidth Pulse-repetition interval Illumination time Emitter revisit time Desired EW revisit time = Emitter illumination time Desired EW dwell = M × emitter PRI (M is an integer)

6. Scenario-numbers • Number of emitters: 2000 • Emitters to track: 50-200 • Average dwell time: 3-30 msec • Revisits per second: 2 • If tracking 50 emitters, using 10mSec dwell times each, how many revisits per Sec? • 1,000 ms/(50 x 10ms) = 2 max.

7. Fixed Scan Scheduler (FSS) Definition: Using prior knowledge, mission planners construct a Static, Mission-Specific Scan Schedule or a “Fixed Scan Schedule” off-line for use during future missions.

8. Fixed Scan Schedule Construction

9. FSS: Example Schedule A1 B1 A2 B2 A3 C1 A4

10. Parameters - continued Assume a K number of EW receivers are provided, each covering an instantaneous bandwidth f. Assume the spectral region of surveillance covers a frequency range from f1 to f2. Therefore, the surveillance coverage consists of L number of bands any K of which can be covered instantaneously If then we have a problem (cannot cover all) A threat list of emitters of interest shows that they operate in only L’ of the L frequency bands from f1 to f2.

11. Parameters -cont. Frequency band l of the L‘ bands contains an Ml number of emitters, each having a desired revisit time Tlm and desired dwell lm , m = 1, 2, , Ml . f1 f2 If lm > ln , then whenever the EW system revisits emitter m, it will also revisit emitter n, provided that revisit time is Tlmand it is the smallest In other words: Trevisit = min {Tlm ,Tln} dwell = max {lm ,ln}

12. Constraint: = Emitter illumination time Number of nth-emitter pulses desired to be available for opportunity of interception. cannot satisfy the constraint, must compromise with Constraints on parameters Tn EW revisit time for nth emitter. n EW dwell time for nth emitter. Consequence is degradation of probability of intercept.

13. What follows There are two aspects to scheduling receivers: performance of a receiver (Measure of Effectiveness (MOE), when and for how long) and the value of that performace to the system (Figure of Merit (FOM), how important is that threat) The following slides focus on MOEs for receivers

14. Metric of Scan-Schedule Performance Example 1 (one pulse) Rn Event that EW receiver is ready to receive transmission from nth emitter when transmission occurs. In Event that EW receiver intercepts transmission from nth emitter.

15. Example 2 (three pulses) R Event that the EW receiver is ready to receive emitter transmission when it occurs. p Conditional probability of EW receiver detecting a pulse when it occurs, given that the EW receiver is queued to receive it. I Event that EW receiver detects at least three of the emitter pulses. Greatest integer in x.

16. number of emitter pulses. Example 3 (Mn pulses) Minimum number of pulses intercepted that is required to perform task (detection, emitter identification, direction finding). Suppose EW receiver dwells long enough for emitter to transmit Mn pulses. pn Probability of detecting a pulse from nth emitter. The longer the dwell n, the larger Mn and the the higher PIn.

17. MOEs • Now we focus on MOEs for the Scheduler • The following slides need to be reviewed

18. Figures of Merit Resource Time Detection range; Probability of report; Probability of Intercept Search Accuracy of track: Direction, signal parameters (frequency, pulsewidth, pulse-repetition interval, modulation parameters, etc.) Track Tasks Whether or not performed and consequences if not performed (degradation in FOM of other two tasks.) Compensation A scan state services one or multiple emitters simultaneously. Compensation is performed during other scan states. Tn EW revisit time for nth scan state. n EW dwell time for nth scan state. Constraints Probability of mis-identifying a non-threat as a threat must be kept very low. For example, classifying a civilian airliner as a lethal threat must be vanishingly small before defensive action is initiated. Resources, Tasks and Constraints

19. Two scenarios - two sets of MOEs MISSION Ingress Egress Must survive to complete mission [destroying target(s)]. Must survive to get home intact.

20. INGRESS (Surviving to hunt/destroy targets) EW Search (Searching to protect against lethal threats) RESOURCE Required Reaction Time to Survive Probability of Surviving, given that threat is encountered: P(S|) Probability of encountering threat: P() Dwell Time Estimated Lethality Revisit Time Threats Th1 Severe P(1) P(S1|1) Th2 P(S2|2) P(2) Moderate ThN P(SN|N) P(N) Probability of surviving ingress part of mission The shorter the dwell, or the longer the revisit time, the longer will be the reaction time, and the lower will be the probability of surviving a threat when it is encountered. EGRESS is similar

21. RESOURCE Probability of Detection, given that target is encountered: P(D|) Targets of Prey Probability of encountering target: P() Dwell Time Value of Destroying Revisit Time v1 EW Search (Searching for prey) Tp1 P(D1|1) P(1) Tp2 v2 P(D2|2) P(2) TpN vN P(DN|N) P(N) RESOURCE The longer the dwell time, or the shorter the track-update interval, the less likely will be a loss of track, and the more likely will be target destruction. Targets of Prey Probability of Kill given detection: P(K|D) Dwell Time Value of Destroying Track-Update Interval Tp1 v1 P(K1|D1) EW Track & Target Kill Tp2 v2 P(K2|D2) TpN vN P(KN|DN) INGRESS (Success of hunt)

22. INGRESS, Cont. (Success of hunt) Conditional mathematical expectation of total value of destruction, given that hunter survives

23. From Fixed to Dynamic Scan Scheduling • There are many reasons for having dynamic scheduling • New targets have been detected and need to be tracked • The plane (with receivers on board) is moving and thus the relative illumination times • of various targets have changed (?) • Terrain masking can suddenly disappear, as the aircraft travels, thereby exposing aircraft • to being detected • Scheduler’s FOM (Figure of Merit) function changes since some emitters shifted their • operational mode: • Surveillance mode PRF (1 kHz) • Pulse Doppler PRF (10 to 20 kHz) • Precision tracking (pencil antenna beam) pulse-Doppler PRF • Additionally, emitters can change their characteristics • Changing PRI (staggering), but fixed frequency • Modulation • Initial goal: detection? tracking varying emitter parameters? • (As the emitter changes mode (and parameters), lethality can change: Emitter in surveillance mode detects aircraft vehicle and then • changes mode to precision track. When emitter reaches a fire-control solution, a surface-to-air missile is fired, and its radar seeker • begins transmitting.) • Can simulate varying parameters with a dynamic process?

24. Dynamic Scan Scheduler

25. Dynamic Scheduling through Negotiation • Goal - mission: maximize probability of success of mission • ingress: maximize probabilityof destruction of target(s) • egress: maximize probability of survival (return home intact) • Goal must translate to a negotiation problem (conflicting • objectives for negotiating parties • Sensor agent: maximize accuracy of tracking according to • priorities - initial goal • maximize probability of survival - next goal • minimize ratio of dwell time to revisit time • Threat agent: minimize accuracyof tracking - initial goal • maximize probability of intercept - next goal • maximize ratio of dwell time to revisit time

26. Negotiation Configuration . . . Sensor Agent Threat Agents

27. Schedule Negotiation • Example (ingress):current threat situation = threat prob. vector Maximize • Seen as a resource sharing problem: • resource = sensor utilization • how much of it is available: 1 • to be shared between N threat agents • each of these agents gets a fraction (n/Tn) of the resource,where n = dwell-time allocated and Tn=revisit time allocated to the agent. (P(1), P(2)…,P(N)) Constraint:

28. Schedule Negotiation (detection) • Sensor agent: minimize (n/Tn) • weigh according to threat priority • as a first approximation • subject to constraints • Threat agent: maximize (n/Tn) • Open issues: • ensure that real-time constraints are met • how to take probability of threats (I.e P(e)) into account • Dynamic scheduling: • renegotiate the schedule when threat probability vector changes